WO2019184479A1 - 一种车辆定损的方法、装置及设备 - Google Patents

一种车辆定损的方法、装置及设备 Download PDF

Info

Publication number
WO2019184479A1
WO2019184479A1 PCT/CN2018/123336 CN2018123336W WO2019184479A1 WO 2019184479 A1 WO2019184479 A1 WO 2019184479A1 CN 2018123336 W CN2018123336 W CN 2018123336W WO 2019184479 A1 WO2019184479 A1 WO 2019184479A1
Authority
WO
WIPO (PCT)
Prior art keywords
video image
vehicle
damage
target vehicle
loss
Prior art date
Application number
PCT/CN2018/123336
Other languages
English (en)
French (fr)
Inventor
郭之友
Original Assignee
阿里巴巴集团控股有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 阿里巴巴集团控股有限公司 filed Critical 阿里巴巴集团控股有限公司
Publication of WO2019184479A1 publication Critical patent/WO2019184479A1/zh
Priority to US16/918,888 priority Critical patent/US11087138B2/en
Priority to US17/370,984 priority patent/US20210334548A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
    • G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
    • G06V20/625—License plates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/08—Detecting or categorising vehicles

Definitions

  • the present specification relates to the field of computer technology, and in particular, to a method, device and device for determining a vehicle loss.
  • the vehicle damage is based on the vehicle construction principle, through scientific and systematic professional inspection, testing and survey means. Comprehensive analysis of collision and accident scenes, using vehicle estimated damage data and maintenance data, scientific pricing estimation of vehicle collision repair.
  • the fixed damage of the vehicle involves many aspects of technology and benefits such as maintenance, manufacturing and owner. It is a prominent part of the whole auto insurance service. Therefore, it is very important to determine the damage of the vehicle.
  • the insurance institution will set up a vehicle for the loss of the vehicle. When the insured vehicle has a traffic accident, the insurance agency will dispatch the vehicle to the site to check the damage.
  • the purpose of embodiments of the present specification is to provide a method, apparatus and apparatus for vehicle damage to provide a more efficient vehicle loss planning scheme.
  • a method for determining a vehicle loss provided by an embodiment of the present specification, the method comprising:
  • the target vehicle is subjected to a loss based on the first video image and the second video image.
  • the second video image includes a third video image and a fourth video image
  • the continuing to acquire a second video image related to the damage of the target vehicle, and the second video image conforms to predetermined requirements for capturing a vehicle damage feature including:
  • the third video image is capable of determining a damaged portion of the target vehicle, continuing to collect a fourth video image for determining a degree of damage of the target vehicle;
  • the fourth video image is capable of determining the degree of damage of the target vehicle, it is determined that the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the first video image meets a predetermined requirement of the photographing identifier, and includes:
  • the extracted image features match the characteristics of the set vehicle identification, it is determined that the first video image meets the predetermined requirements of the shot identification.
  • the features of the vehicle identification include a combination of one or more of the following: a license plate number, a headlight, a hub, a door handle, a vehicle taillight, a vehicle rearview mirror, a fuel tank cap, and a charging port.
  • the method further includes: if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the method further includes:
  • Determining the target vehicle based on the first video image and the second video image, if the second video image meets a predetermined requirement for capturing a vehicle damage feature including:
  • the target vehicle is subjected to a loss based on the first video image and the second video image.
  • the first video image meets a predetermined requirement of the photographing identifier, and includes:
  • the second region is highlighted to determine that the first video image meets a predetermined requirement for the photographic identity.
  • the second video image meets predetermined requirements for capturing a vehicle damage feature, including:
  • the fourth region is highlighted to determine that the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the determining, by the first video image and the second video image, the damage to the target vehicle comprises:
  • a device for determining a vehicle damage provided by an embodiment of the present specification, the device includes:
  • a first video collection module configured to collect a first video image that includes an identifier of a target vehicle to be determined
  • a second video capture module configured to continue to collect a second video image related to the damage of the target vehicle if the first video image meets a predetermined requirement of the photographing identifier
  • a vehicle damage module configured to perform a loss on the target vehicle based on the first video image and the second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the second video image includes a third video image and a fourth video image
  • the vehicle loss module includes:
  • a third video collection unit configured to continue to collect a third video image for determining a damaged portion of the target vehicle
  • a fourth video collection unit configured to continue to collect a fourth video image for determining a degree of damage of the target vehicle if the third video image is capable of determining a damage location of the target vehicle;
  • a determining unit configured to determine that the second video image meets a predetermined requirement for capturing a vehicle damage feature if the fourth video image is capable of determining a degree of damage of the target vehicle.
  • the second video collection module includes:
  • a feature extraction unit configured to extract an image feature related to the identifier of the target vehicle from the first video image
  • a judging unit configured to determine that the first video image meets a predetermined requirement of the photographing identifier if the extracted image feature matches the feature of the set vehicle identifier.
  • the features of the vehicle identification include a combination of one or more of the following: a license plate number, a headlight, a hub, a door handle, a vehicle taillight, a vehicle rearview mirror, a fuel tank cap, and a charging port.
  • the device further includes:
  • a video image sending module configured to send the second video image to a vehicle loss server, so that the vehicle damage server determines whether the second video image meets a predetermined requirement for capturing a vehicle damage feature, and obtains a determination result
  • a determination result receiving module configured to receive the determination result sent by the fixed loss server
  • the vehicle damage module is configured to: if the determination result indicates that the second video image meets a predetermined requirement for capturing a vehicle damage feature, based on the first video image and the second video image The vehicle is subjected to a fixed loss.
  • the second video collection module includes:
  • a first area determining unit configured to determine, from the first video image, a first area where the identifier of the target vehicle is located
  • a first filling unit configured to fill the first area by a preset capturing unit, to obtain a second area composed of a capturing unit;
  • a first determining unit configured to: if the video image in the second region meets a predetermined requirement of the photographing identifier, highlight the second region to determine that the first video image meets a predetermined requirement of the photographing identifier.
  • the vehicle loss module includes:
  • a third area determining unit configured to determine, from the second video image, a third area related to damage of the target vehicle
  • a second filling unit configured to fill the third area by a preset capturing unit, to obtain a fourth area composed of a capturing unit
  • a second determining unit configured to: if the video image in the fourth region meets a predetermined requirement for capturing a vehicle damage feature, highlighting the fourth region to determine that the second video image conforms to a photographing vehicle damage feature Booking requirements.
  • the vehicle loss module includes:
  • a video image transmitting unit configured to send the first video image and the second video image to a vehicle loss server, so that the vehicle loss server is configured according to the first video image and the second video image Determining the target vehicle to obtain a loss result of the target vehicle;
  • a fixed loss result receiving unit configured to receive the fixed loss result sent by the fixed loss server.
  • a memory arranged to store computer executable instructions that, when executed, cause the processor to:
  • the target vehicle is subjected to a loss based on the first video image and the second video image.
  • the embodiment of the present specification collects a first video image including an identifier of a target vehicle to be determined, and if the first video image meets a predetermined requirement of the photographing identifier, continues to collect the target vehicle.
  • Damage-related second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image, such that when the user only needs to pass the imaging device
  • the video of the target vehicle to be damaged can complete the damage to the target vehicle.
  • the insurance organization is not required to dispatch the corresponding vehicle damage personnel to the site for investigation and damage, thus saving the insurance organization a lot of human resources and material resources. Resources, and the vehicle damage is analyzed by the terminal device or the server to analyze the video images uploaded by the user, which saves the time required for the vehicle to determine the damage, and improves the efficiency of the vehicle's loss.
  • 1 is an embodiment of a method for determining a vehicle's loss according to the present specification
  • FIG. 2A is a schematic diagram of a video capture interface in a vehicle loss process according to the present specification
  • 2B is a schematic diagram of a video capture interface when a video image is started during a vehicle loss determination process according to the present specification
  • 2C is a schematic diagram of a video capture interface that enters the next shooting after a video image capture in one stage of the vehicle's fixed loss process is completed;
  • 2D is a schematic diagram of a capture unit filling a first region or a third region during a vehicle damage process according to the present specification
  • FIG. 4 is still another embodiment of a method for determining a vehicle loss according to the present specification
  • Figure 5 is an embodiment of a device for determining a vehicle in the present specification
  • FIG. 6 is a schematic diagram of an apparatus for determining a vehicle's loss in the present specification.
  • Embodiments of the present specification provide a method, device, and device for vehicle damage.
  • the embodiment of the present disclosure provides a method for determining a vehicle loss.
  • the execution body of the method may be a terminal device, or may be jointly performed by a terminal device and a server, where the terminal device may be, for example, a personal computer.
  • the device may also be a mobile terminal device such as a mobile phone or a tablet computer, and the terminal device may be a terminal device used by the user.
  • the server may be a stand-alone server or a server cluster composed of multiple servers, and the server may be a server for performing vehicle damage.
  • This method can be used in processes such as vehicle loss determination.
  • the method may specifically include the following steps:
  • step S102 a first video image including the identification of the target vehicle to be determined is acquired.
  • the target vehicle may be any vehicle that causes damage after a collision of the vehicle.
  • the identification may be information for determining the identity of the target vehicle, such as the license plate number of the target vehicle or the engine number of the target vehicle, and the like.
  • the first video image may be an image of a video taken by the imaging device.
  • the fixed damage of the vehicle involves many aspects of technology and benefits such as maintenance, manufacturing and owner. It is a prominent part of the entire auto insurance service. Surveys and damages exist to determine the accident losses, including the authenticity of the losses, the actual extent of the losses, the extent of repairs or compensation, and so on. In order to do a good job of vehicle survey and damage, the insurance organization will set up a vehicle to determine the loss. When the insured vehicle has a traffic accident, the insurance agency will dispatch the vehicle to the site to check the damage.
  • the demand for vehicle-damaged personnel by insurance institutions is increasing, and the requirements for vehicle-damaged personnel are becoming more and more standardized.
  • the embodiment of the present specification provides a method for determining the damage of a vehicle, that is, the frequent scheduling of the personnel of the insurance institution can be saved, and the efficiency of the vehicle in the morning of the fixed loss can be improved, which may specifically include the following contents:
  • the distance of the informant such as the driver of the vehicle or the occupant
  • the distance of the informant is much closer to the distance from the vehicle of the insurance institution to the target vehicle.
  • the informant can report the true information of the target vehicle, meet the requirements of the damage assessment and the required normative evidence, the insurance institution does not need to dispatch or dispatch the vehicle to the target vehicle, thus reducing the insurance organization's The loss of human resources, but also can improve the efficiency of vehicle damage. Therefore, a mechanism for reporting or uploading vehicle loss information can be set up. Through this mechanism, users can be guided to report the standard vehicle damage information.
  • a possible implementation is described as follows:
  • the information related to the vehicle loss can be reported by using a video image.
  • the user terminal device may be provided with a trigger button of the vehicle loss information reporting mechanism.
  • the corresponding application program may be written in a computer programming language based on the vehicle loss information reporting mechanism.
  • the trigger button of the vehicle loss information reporting mechanism may be clicked, or the corresponding application program may be activated to trigger the execution of the vehicle loss information reporting mechanism.
  • the terminal device can perform the vehicle loss information reporting mechanism.
  • the terminal device can activate the camera and open the video capturing function to capture a video image through the camera.
  • the display interface of the terminal device can be set.
  • the user may perform a corresponding operation by using the prompt information, wherein the prompt information may be used to prompt the user to capture the identifier of the target vehicle, etc., so that the terminal device may collect the identifier of the target vehicle including the target to be determined.
  • a video image may be used to prompt the user to capture the identifier of the target vehicle including the target to be determined.
  • the prompt information prompts the user to capture the license plate number of the target vehicle, so that the user can point the camera of the terminal device to the license plate number of the target vehicle for video shooting to obtain the first video image, as shown in FIG. 2A and FIG. 2B.
  • the identification is a license plate number
  • a rectangular area may be provided in the camera preview interface of the terminal device.
  • the user may be prompted to place the image of the license plate number in the rectangular area to facilitate subsequent Identification of the license plate number.
  • step S104 if the first video image meets the predetermined requirement of the photographing identifier, the second video image related to the damage including the target vehicle is continuously collected.
  • the second video image may be an image of a video captured by the imaging device and including a damage condition of the target vehicle, wherein the target vehicle damage condition may include a damaged portion, a degree of damage, and the like.
  • the predetermined requirement of the photographing logo may be set according to actual conditions, for example, the license plate number, and the predetermined requirement of the photographing logo may be a feature of the license plate number, and may include: a relatively regular rectangle (where a parallelogram is used in non-planar shooting) ), blue or white on the blue background, Chinese + white point + 5 combinations of English and / or numbers.
  • the terminal device may perform image analysis on the captured first video image, that is, the target region of the captured target vehicle in the video window may be calculated in real time, and the captured image is captured.
  • the combination of the cells fills the area of the target area, so that the feature corresponding to the identifier existing in the first video image can be captured, and then the corresponding area can be locked, and the area is further identified and judged, thereby determining the first video. Whether the image meets the predetermined requirements for the shot mark.
  • the identification is a license plate number
  • the terminal device can perform image analysis on the captured first video image, that is, the target region of the target vehicle in the video window that matches the “relative regular rectangle” of the license plate number can be calculated in real time, Capturing a combination of display units, filling an area of the target area, so that a feature existing in the first video image that matches the "relatively regular rectangle" of the license plate number can be captured, and then the rectangular area of the rule can be locked, and The rectangular area of the rule is further identified, that is, whether the rectangular area of the rule is a blue-white or yellow-black text, and whether the rectangular area of the rule includes Chinese + white point + 5 digits of English and/or number Combine or the like to determine whether the first video image meets the predetermined requirements of the photographing logo.
  • the rectangular area of the rule is a blue-white or yellow-black text and contains a combination of Chinese + white point + 5 digits of English and/or numbers, it is determined that the first video image meets the predetermined requirement of the shooting identifier, otherwise, A video image does not meet the predetermined requirements for the shot mark.
  • the intuitive processing method of whether the first video image meets the predetermined requirement of the photographing identifier may include various types, for example, performing color changing processing on the target area, that is, if it is determined that the first video image meets a predetermined requirement of the photographing identifier, the above rule may be The rectangular area changes from gray to red, etc., so that the user can know in time whether the captured video image meets the specifications or requirements.
  • the terminal device may start the prompt information of the next guiding.
  • the prompt information of the next step may be set in the display interface of the terminal device, and the prompt is The user can continue to take a corresponding video image, wherein the prompt information can be used to prompt the user to take a damage condition of the target vehicle, etc., so that the terminal device can collect a second video image including the damage location of the target vehicle and the degree of damage.
  • step S106 if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image.
  • the predetermined requirement for photographing the damage feature of the vehicle may be set according to actual conditions, for example, the license plate number, and the predetermined requirement of the photographing identifier may be a feature of the license plate number, and may include: a relatively regular rectangle (wherein, in a non-planar shot) Time is a parallelogram), white on a blue background or black on a yellow background, Chinese + white point + a combination of 5 English and / or numbers.
  • the terminal device may perform image analysis on the captured second video image, that is, the target vehicle captured in the video window may be calculated in real time.
  • the target area can fill the area of the target area by capturing the combination of the display units, so that the vehicle damage feature existing in the second video image can be captured, and then the corresponding area can be locked and the area can be further identified and judged.
  • a determination is made as to whether the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the intuitive processing method of whether the second video image meets the predetermined requirement for capturing the damage feature of the vehicle may include various types, such as performing color changing processing on the target area.
  • the terminal device may prompt the user that the current shooting has been completed, and if the user instructs to continue shooting, the video image capturing may be continued through the processes of step S104 and step S106 described above, if When the user instructs to end the shooting, the terminal device may acquire the first video image and the second video image, and perform image analysis on the first video image and the second video image respectively to determine the component of the target vehicle damage and the degree of damage, thereby formulating Maintenance plan, repair price, and claims for car insurance, so as to achieve the purpose of damage to the target vehicle.
  • the process of performing the loss on the target vehicle may be performed in the terminal device or may be performed by the server.
  • the terminal device acquires the first video image and the second video image
  • the first video image and the second video image may be sent to the vehicle loss server, and the vehicle loss server receives the first video image.
  • the first video image and the second video image may be subjected to video analysis to determine the component of the target vehicle damage and the degree of damage, thereby formulating a maintenance plan, a repair price, and a claim for the car insurance.
  • the vehicle loss determination result can be sent to the terminal device, so that the data processing pressure of the terminal device can be alleviated and the data processing efficiency can be improved.
  • the embodiment of the present specification provides a method for determining a vehicle loss, collecting a first video image including an identifier of a target vehicle to be determined, and if the first video image meets a predetermined requirement of the photographing identifier, continuing to collect damage related to the target vehicle.
  • a second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image, such that when the user only needs to be determined by the camera device The target vehicle captures the video image, and the fixed damage to the target vehicle can be completed.
  • the insurance organization does not need to dispatch the corresponding vehicle damage personnel to the site for investigation and damage, so that the insurance organization saves a lot of human resources and material resources, and
  • the vehicle damage is determined by analyzing the video image uploaded by the user through the terminal device or the server, which saves the time required for the vehicle to determine the damage, and improves the efficiency of the vehicle damage.
  • the embodiment of the present disclosure provides a method for determining a vehicle loss.
  • the execution body of the method may be a terminal device, where the terminal device may be a device such as a personal computer, or may be moved, such as a mobile phone or a tablet computer.
  • a terminal device which can be a terminal device used by a user. This method can be used in processes such as vehicle loss determination. The method may specifically include the following steps:
  • step S302 a first video image including the identification of the target vehicle to be determined is acquired.
  • the vehicle identification feature may include one or more of the following combinations: a license plate number, a headlight, a hub, a door handle, a vehicle taillight, a vehicle rearview mirror, a fuel tank cap and a charging port, etc.
  • the vehicle identification The feature is not limited to the above, and may include other information capable of proving the identity of the target vehicle, such as an engine number or a vehicle identification code (VIN).
  • VIN vehicle identification code
  • the content of the step S302 is the same as the content of the step S102 in the first embodiment.
  • step S304 image features related to the identification of the target vehicle are extracted from the first video image.
  • a feature extraction algorithm of a video image may be set in the terminal device, and the feature extraction algorithm may extract information that is characteristic in the video image.
  • the terminal device may retrieve a preset feature extraction algorithm, and the feature extraction algorithm may analyze the first video image, and may extract the feature from the first video image.
  • the information related to the identification of the target vehicle may be extracted from the extracted information containing the characteristics according to the information related to the identification of the target vehicle.
  • step S306 if the extracted image feature matches the feature of the set vehicle identification, it is determined that the first video image meets the predetermined requirement of the shot identification.
  • a feature library of the vehicle may be stored in the terminal device, and the feature library may store a feature of the vehicle identifier.
  • the feature library may store related features of the license plate, related features of the headlight, and a hub.
  • Related features of the hub, door handle, vehicle taillight, vehicle rear view mirror, fuel tank cap or charging port may include: appearance style features, internal structural style features, and the like.
  • the extracted image features may be matched with the features of the vehicle identifier stored in the feature library, if the extracted image features and the vehicle stored in the feature library are If the features of the logo do not match, it indicates that the first video image captured by the user does not meet the specification or requirement.
  • the prompt information may be output to prompt the user to retake the video image, if the extracted image feature and the vehicle identifier stored in the feature library are The matching of the features indicates that the first video image captured by the user conforms to the specification or requirement, and at this time, the first video image may be stored.
  • the foregoing process for determining whether the first video image meets the predetermined requirement of the photographic identifier may be implemented in a plurality of manners.
  • the following provides an optional processing manner, which may include the following steps 1 to 3.
  • Step one determining a first area where the identifier of the target vehicle is located from the first video image.
  • the first area may be determined by a relevant feature of the identifier of the target vehicle.
  • the identifier of the target vehicle may be referred to the related content.
  • the first area may be the license plate where the license plate number is located.
  • the relevant characteristics of the license plate please refer to the above related content, that is, the relevant features of the license plate may include: a relatively regular rectangle, a blue-white or a yellow-black character, a Chinese + white point + a 5-digit combination of English and/or numbers or more. A combination of English and numbers, etc., therefore, an area having the above characteristics can be found in the first video image, and the above area can be determined as the first area, and the identification of the target vehicle is included in the first area.
  • step two the first area is filled by a preset capturing unit, and a second area composed of the capturing unit is obtained.
  • the preset capturing unit may be a basic component unit of image capturing, and the size of the capturing unit may be set according to actual conditions.
  • the capturing unit may be a square, and the side length of the square may be 1 mm or one or more. The length of the pixel, etc.
  • the first region of the relevant feature of the target vehicle in the target vehicle captured in the video window may be calculated in real time, and the shape of the first region may be determined, and then, as shown in FIG. 2D As shown, a capture unit may be used to fill the area of the area bounded by the first area according to the shape of the first area until the area filled by the plurality of capture units covers the first area, wherein any of the plurality of capture units There is no overlap between the two capture units. Finally, a second region of the capture unit can be obtained.
  • Step 3 If the video image in the second area meets the predetermined requirement of the shooting identifier, the second area is highlighted to determine that the first video image meets the predetermined requirement of the shooting identifier.
  • the extracted image feature may be matched with the feature of the vehicle identifier stored in the feature library, if the extracted image feature and feature If the characteristics of the vehicle identification stored in the library do not match, it indicates that the first video image captured by the user does not meet the specifications or requirements.
  • the prompt information may be output to prompt the user to retake the video image, if the extracted image features and feature libraries are included.
  • the characteristics of the stored vehicle identification are matched.
  • the second area may be highlighted to indicate that the first video image captured by the user meets the specifications or requirements.
  • the specific implementation manner of highlighting the second area may include multiple types. For example, the color of the second area may be changed to a color different from the previous color, such as changing from blue to red, or the like. The second area performs a blinking display or the like.
  • the user can be guided to the next step by changing the operable button or the arrow, such as by an inoperable button or an arrow, or directly unlocking the next step. That is, the user is requested to take a relevant video image of the vehicle damage condition, and the determination of the vehicle damage condition often includes two parts, namely, determining the location of the vehicle damage and determining the degree of the damage. For this reason, the following steps S308 and S310 may be determined. Damage to the target vehicle.
  • step S308 the third video image for determining the damage location of the target vehicle is continuously acquired.
  • the terminal device may display indication information indicating that the user is aligning with the damaged portion of the vehicle for video shooting, and the user may align the camera of the terminal device with the damaged portion of the target vehicle according to the content of the indication information, and continue video shooting.
  • the terminal device can calculate the target area where the damaged part exists in the target vehicle captured in the video window in real time, and then fill the target area by capturing the combination of the display unit.
  • the area of the third video image that can capture the complete damage site of the target vehicle can lock the target area.
  • step S310 if the third video image is capable of determining the damage location of the target vehicle, the fourth video image for determining the degree of damage of the target vehicle continues to be acquired.
  • the third video image may be analyzed, and characteristic information including the characteristic information may be extracted from the third video image.
  • the image feature related to determining the damage part of the target vehicle may be extracted from the extracted characteristic information, and the damaged part of the target vehicle may be determined by the extracted image feature, if The terminal device can determine which position of the target vehicle the damaged part belongs to by the extracted image feature, and can guide the user to enter by using an inoperable button or an arrow to become an operable button or an arrow, or directly unlocking the next step.
  • One-step processing that is, requesting the user to take a video image of the relevant degree of the vehicle.
  • the terminal device may display indication information indicating that the user is aligning the damaged portion of the vehicle to perform damage detail shooting, and the user may align the camera of the terminal device with the damaged portion of the target vehicle according to the content of the indication information, and continue the detailed video. Shooting.
  • the terminal device can calculate the target area of the damage degree of the damaged part in the target vehicle captured in the video window in real time, and then, by capturing the combination of the display units, The area of the target area is filled so that a fourth video image of the degree of damage of the target vehicle can be captured.
  • step S312 if the fourth video image is capable of determining the degree of damage of the target vehicle, the target vehicle is subjected to the loss based on the first video image and the second video image.
  • the second video image may include a third video image and a fourth video image.
  • the fourth video image may be analyzed, and characteristic information including the characteristic information may be extracted from the fourth video image.
  • the image feature related to determining the damage degree of the target vehicle may be extracted from the extracted characteristic information, and the damage degree of the target vehicle may be determined by the extracted image feature, if The terminal device can determine the damage degree of the damaged portion by using the extracted image feature, and the target vehicle can be fixedly damaged based on the first video image and the second video image.
  • the related content of step S106 in the first example is not described here.
  • the foregoing process for determining whether the second video image is to capture a predetermined requirement of the vehicle damage feature may be implemented in various manners.
  • the following provides an optional processing manner, as shown in FIG. 2D, which may specifically include the following steps. One to three.
  • Step one determining a third region related to damage of the target vehicle from the second video image.
  • step two the third area is filled by a preset capturing unit to obtain a fourth area composed of the capturing unit.
  • Step 3 If the video image in the fourth region meets a predetermined requirement for capturing a vehicle damage feature, the fourth region is highlighted to determine that the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the second video image includes the third video image and the fourth video image
  • the third video image can determine the processing of the damaged portion of the target vehicle, based on the above steps 1 to 3, Having: determining, from the third video image, a first sub-area where the damage location of the target vehicle is located; filling the first sub-area by a preset capture unit to obtain a second sub-area composed of the capture unit; if the second sub-area The video image in the middle can determine the damage location of the target vehicle, and the second sub-region is highlighted to determine that the third video image can determine the damage location of the target vehicle.
  • the fourth video image is capable of determining the degree of damage of the target vehicle. Based on the foregoing steps 1 to 3, the third sub-area for determining the degree of damage of the target vehicle from the fourth video image; The unit fills the third sub-region to obtain a fourth sub-region composed of a capture unit; if the video image in the fourth sub-region can determine the damage degree of the target vehicle, the fourth sub-region is highlighted to determine the above.
  • the four video images are capable of determining the damage location of the target vehicle.
  • the third area may include a first sub-area and a third sub-area, and the fourth area may include a second sub-area and a fourth sub-area.
  • Step 1 Send the second video image to the vehicle loss server, so that the vehicle damage server determines whether the second video image meets the predetermined requirement for capturing the vehicle damage feature, and obtains the determination result.
  • the specific processing procedure of the foregoing step 1 may further include: if the first video image meets the predetermined requirement of the shooting identifier, proceeding Collecting a third video image for determining a damage location of the target vehicle; transmitting the third video image to the vehicle loss server, so that the vehicle damage server determines whether the third video image can determine the damage location of the target vehicle, and obtains a determination result.
  • the vehicle fixed loss server may send the determination result to the terminal device.
  • the terminal device continues to collect the fourth video image for determining the damage degree of the target vehicle, and the fourth video image may be sent to the vehicle loss server to
  • the vehicle damage server determines whether the fourth video image can determine the damage degree of the target vehicle, and obtains a determination result, and the vehicle damage server can transmit the determination result to the terminal device.
  • Step 2 Receive the foregoing judgment result sent by the fixed loss server.
  • the processing of the step S312 may be: if the determination result indicates that the second video image meets a predetermined requirement for capturing a vehicle damage feature, based on the first video image and the second video image, The target vehicle performs a loss.
  • the embodiment of the present specification provides a method for determining a vehicle loss, collecting a first video image including an identifier of a target vehicle to be determined, and if the first video image meets a predetermined requirement of the photographing identifier, continuing to collect damage related to the target vehicle.
  • a second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image, such that when the user only needs to be determined by the camera device The target vehicle captures the video image, and the fixed damage to the target vehicle can be completed.
  • the insurance organization does not need to dispatch the corresponding vehicle damage personnel to the site for investigation and damage, so that the insurance organization saves a lot of human resources and material resources, and
  • the vehicle damage is determined by analyzing the video image uploaded by the user through the terminal device or the server, which saves the time required for the vehicle to determine the damage, and improves the efficiency of the vehicle damage.
  • the embodiment of the present disclosure provides a method for determining a vehicle loss.
  • the execution body of the method may be a terminal device and a vehicle loss server.
  • the terminal device may be a device such as a personal computer, or may be a mobile phone.
  • a mobile terminal device such as a tablet computer, which can be a terminal device used by a user.
  • the vehicle loss server may be a stand-alone server or a server cluster composed of a plurality of servers, and the vehicle loss server may be a server for performing vehicle damage.
  • This method can be used in processes such as vehicle loss determination.
  • the method may specifically include the following steps:
  • step S402 the terminal device collects a first video image including an identification of the target vehicle to be determined.
  • the vehicle identification feature may include a combination of one or more of the following: a license plate number, a headlight, a hub, a door handle, a vehicle taillight, a vehicle rearview mirror, a fuel tank cap, and a charging port.
  • step S404 the terminal device extracts image features related to the identification of the target vehicle from the first video image.
  • step S406 if the extracted image feature matches the feature of the set vehicle identification, the terminal device determines that the first video image meets the predetermined requirement of the shooting identification.
  • step S408 the terminal device continues to collect a third video image for determining the damage location of the target vehicle.
  • step S410 if the third video image is capable of determining the damage location of the target vehicle, the terminal device continues to acquire a fourth video image for determining the degree of damage of the target vehicle.
  • step S408 and the step S410 For the processing of the foregoing step S408 and the step S410, refer to the related content of the step S308 and the step S310 in the second embodiment, and details are not described herein again.
  • the process of evacuating the loss can be completed by the server (ie, the vehicle loss server).
  • the server ie, the vehicle loss server.
  • step S412 if the fourth video image is capable of determining the degree of damage of the target vehicle, the terminal device transmits the first video image and the second video image to the vehicle loss server, wherein the second video image includes the third video image and The fourth video image.
  • Step 1 Send the second video image to the vehicle loss server to cause the vehicle damage server to determine whether the second video image meets a predetermined requirement for capturing the vehicle damage feature, and obtain a judgment result.
  • the specific processing procedure of the foregoing step 1 may further include: if the first video image meets the predetermined requirement of the shooting identifier, proceeding Collecting a third video image for determining a damage location of the target vehicle; transmitting the third video image to the vehicle loss server, so that the vehicle damage server determines whether the third video image can determine the damage location of the target vehicle, and obtains a determination result.
  • the vehicle fixed loss server may send the determination result to the terminal device.
  • the terminal device continues to collect the fourth video image for determining the damage degree of the target vehicle, and the fourth video image may be sent to the vehicle loss server to
  • the vehicle damage server determines whether the fourth video image can determine the damage degree of the target vehicle, and obtains a determination result, and the vehicle damage server can transmit the determination result to the terminal device.
  • Step 2 Receive the foregoing judgment result sent by the fixed loss server.
  • the processing of the above step S412 may be: if the determination result indicates that the second video image meets a predetermined requirement for capturing a vehicle damage feature, the terminal device sets the first video image and the second video image. Send to the vehicle to determine the loss server.
  • step S414 the vehicle damage server performs a loss on the target vehicle according to the first video image and the second video image to obtain a loss result of the target vehicle.
  • the vehicle fixed loss server may separately perform video analysis on the first video image and the second video image to determine The component damage and damage degree of the target vehicle damage, and thus the vehicle damage determination results such as the maintenance plan, the repair price, and the claim for the car insurance, so that the processing efficiency of the vehicle damage can be improved.
  • step S416 the terminal device receives the above-mentioned fixed loss result sent by the fixed loss server.
  • the embodiment of the present specification provides a method for determining a vehicle loss, collecting a first video image including an identifier of a target vehicle to be determined, and if the first video image meets a predetermined requirement of the photographing identifier, continuing to collect damage related to the target vehicle.
  • a second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image, such that when the user only needs to be determined by the camera device The target vehicle captures the video image, and the fixed damage to the target vehicle can be completed.
  • the insurance organization does not need to dispatch the corresponding vehicle damage personnel to the site for investigation and damage, so that the insurance organization saves a lot of human resources and material resources, and
  • the vehicle damage is determined by analyzing the video image uploaded by the user through the terminal device or the server, which saves the time required for the vehicle to determine the damage, and improves the efficiency of the vehicle damage.
  • the embodiment of the present specification further provides a device for determining the damage of the vehicle, as shown in FIG. 5 .
  • the device for determining the damage of the vehicle includes: a first video capture module 501, a second video capture module 502, and a vehicle damage module 503, wherein:
  • a first video capture module 501 configured to collect a first video image that includes an identifier of a target vehicle to be determined
  • the second video capture module 502 is configured to continue to collect a second video image related to the damage of the target vehicle if the first video image meets a predetermined requirement of the photographing identifier;
  • the vehicle damage module 503 is configured to perform a loss on the target vehicle based on the first video image and the second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the second video image includes a third video image and a fourth video image
  • the vehicle damage module 503 includes:
  • a third video collection unit configured to continue to collect a third video image for determining a damaged portion of the target vehicle
  • a fourth video collection unit configured to continue to collect a fourth video image for determining a degree of damage of the target vehicle if the third video image is capable of determining a damage location of the target vehicle;
  • a determining unit configured to determine that the second video image meets a predetermined requirement for capturing a vehicle damage feature if the fourth video image is capable of determining a degree of damage of the target vehicle.
  • the second video collection module 502 includes:
  • a feature extraction unit configured to extract an image feature related to the identifier of the target vehicle from the first video image
  • a judging unit configured to determine that the first video image meets a predetermined requirement of the photographing identifier if the extracted image feature matches the feature of the set vehicle identifier.
  • the characteristics of the vehicle identification include a combination of one or more of the following: a license plate number, a headlight, a hub, a door handle, a vehicle tail light, a vehicle rear view mirror, a fuel tank cover, and a charging port.
  • the device further includes:
  • a video image sending module configured to send the second video image to a vehicle loss server, so that the vehicle damage server determines whether the second video image meets a predetermined requirement for capturing a vehicle damage feature, and obtains a determination result
  • a determination result receiving module configured to receive the determination result sent by the fixed loss server
  • the vehicle damage module is configured to: if the determination result indicates that the second video image meets a predetermined requirement for capturing a vehicle damage feature, based on the first video image and the second video image The vehicle is subjected to a fixed loss.
  • the second video collection module 502 includes:
  • a first area determining unit configured to determine, from the first video image, a first area where the identifier of the target vehicle is located
  • a first filling unit configured to fill the first area by a preset capturing unit, to obtain a second area composed of a capturing unit;
  • a first determining unit configured to: if the video image in the second region meets a predetermined requirement of the photographing identifier, highlight the second region to determine that the first video image meets a predetermined requirement of the photographing identifier.
  • the vehicle damage module 503 includes:
  • a third area determining unit configured to determine, from the second video image, a third area related to damage of the target vehicle
  • a second filling unit configured to fill the third area by a preset capturing unit, to obtain a fourth area composed of a capturing unit
  • a second determining unit configured to: if the video image in the fourth region meets a predetermined requirement for capturing a vehicle damage feature, highlighting the fourth region to determine that the second video image conforms to a photographing vehicle damage feature Booking requirements.
  • the vehicle damage module 503 includes:
  • a video image transmitting unit configured to send the first video image and the second video image to a vehicle loss server, so that the vehicle loss server is configured according to the first video image and the second video image Determining the target vehicle to obtain a loss result of the target vehicle;
  • a fixed loss result receiving unit configured to receive the fixed loss result sent by the fixed loss server.
  • the embodiment of the present specification provides a device for determining a vehicle damage, which acquires a first video image including an identifier of a target vehicle to be determined, and if the first video image meets a predetermined requirement of the photographing identifier, continues to collect damage related to the target vehicle.
  • a second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image, such that when the user only needs to be determined by the camera device The target vehicle captures the video image, and the fixed damage to the target vehicle can be completed.
  • the insurance organization does not need to dispatch the corresponding vehicle damage personnel to the site for investigation and damage, so that the insurance organization saves a lot of human resources and material resources, and
  • the vehicle damage is determined by analyzing the video image uploaded by the user through the terminal device or the server, which saves the time required for the vehicle to determine the damage, and improves the efficiency of the vehicle damage.
  • the device for determining the damage of the vehicle provided by the embodiment of the present invention is based on the same idea.
  • the embodiment of the present specification further provides a device for determining the damage of the vehicle, as shown in FIG. 6 .
  • the device for determining the damage of the vehicle may be the terminal device provided by the above embodiment.
  • a device that is destructive to a vehicle may vary considerably depending on configuration or performance, and may include one or more processors 601 and memory 602 in which one or more storage applications or data may be stored.
  • the memory 602 can be short-lived or persistent.
  • An application stored in memory 602 may include one or more modules (not shown), each of which may include a series of computer executable instructions in a device that is destructive to the vehicle.
  • the processor 601 can be configured to communicate with the memory 602 to execute a series of computer executable instructions in the memory 602 on a device that is destructive to the vehicle.
  • the device for vehicle damage may also include one or more power sources 603, one or more wired or wireless network interfaces 604, one or more input and output interfaces 605, one or more keyboards 606.
  • the device for determining the damage of the vehicle includes a memory, and one or more programs, wherein one or more programs are stored in the memory, and one or more programs may include one or more modules, and Each module can include a series of computer executable instructions in a device that is destructive to the vehicle, and configured to be executed by one or more processors.
  • the one or more programs are included for performing the following computer executable instructions:
  • the target vehicle is subjected to a loss based on the first video image and the second video image.
  • the second video image includes a third video image and a fourth video image
  • the continuing to acquire a second video image related to the damage of the target vehicle, and the second video image conforms to predetermined requirements for capturing a vehicle damage feature including:
  • the third video image is capable of determining a damaged portion of the target vehicle, continuing to collect a fourth video image for determining a degree of damage of the target vehicle;
  • the fourth video image is capable of determining the degree of damage of the target vehicle, it is determined that the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the first video image meets a predetermined requirement of the photographing identifier, and includes:
  • the extracted image features match the characteristics of the set vehicle identification, it is determined that the first video image meets the predetermined requirements of the shot identification.
  • the characteristics of the vehicle identification include a combination of one or more of the following: a license plate number, a headlight, a hub, a door handle, a vehicle tail light, a vehicle rear view mirror, a fuel tank cover, and a charging port.
  • the method further includes:
  • Determining the target vehicle based on the first video image and the second video image, if the second video image meets a predetermined requirement for capturing a vehicle damage feature including:
  • the target vehicle is subjected to a loss based on the first video image and the second video image.
  • the first video image meets a predetermined requirement of the photographing identifier, and includes:
  • the second region is highlighted to determine that the first video image meets a predetermined requirement for the photographic identity.
  • the second video image meets a predetermined requirement for capturing a vehicle damage feature, and includes:
  • the fourth region is highlighted to determine that the second video image meets a predetermined requirement for capturing a vehicle damage feature.
  • the determining, by the first video image and the second video image, the damage to the target vehicle includes:
  • the embodiment of the present specification provides a device for determining a vehicle damage, which acquires a first video image including an identifier of a target vehicle to be determined, and if the first video image meets a predetermined requirement of the photographing identifier, continues to collect damage related to the target vehicle.
  • a second video image if the second video image meets a predetermined requirement for capturing a vehicle damage feature, the target vehicle is subjected to a loss based on the first video image and the second video image, such that when the user only needs to be determined by the camera device The target vehicle captures the video image, and the fixed damage to the target vehicle can be completed.
  • the insurance organization does not need to dispatch the corresponding vehicle damage personnel to the site for investigation and damage, so that the insurance organization saves a lot of human resources and material resources, and
  • the vehicle damage is determined by analyzing the video image uploaded by the user through the terminal device or the server, which saves the time required for the vehicle to determine the damage, and improves the efficiency of the vehicle damage.
  • PLD Programmable Logic Device
  • FPGA Field Programmable Gate Array
  • HDL Hardware Description Language
  • the controller can be implemented in any suitable manner, for example, the controller can take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (eg, software or firmware) executable by the (micro)processor.
  • computer readable program code eg, software or firmware
  • examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, The Microchip PIC18F26K20 and the Silicone Labs C8051F320, the memory controller can also be implemented as part of the memory's control logic.
  • the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding.
  • Such a controller can therefore be considered a hardware component, and the means for implementing various functions included therein can also be considered as a structure within the hardware component.
  • a device for implementing various functions can be considered as a software module that can be both a method of implementation and a structure within a hardware component.
  • the system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function.
  • a typical implementation device is a computer.
  • the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.
  • embodiments of the present specification can be provided as a method, system, or computer program product.
  • one or more embodiments of the present specification can take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware.
  • one or more embodiments of the present specification can employ a computer program embodied on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer usable program code embodied therein.
  • the form of the product is not limited to disk storage, CD-ROM, optical storage, etc.
  • Embodiments of the present specification are described with reference to flowcharts and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present specification. It will be understood that each flow and/or block of the flowcharts and/or block diagrams, and combinations of flows and/or blocks in the flowcharts and/or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
  • computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
  • embodiments of the present specification can be provided as a method, system, or computer program product.
  • one or more embodiments of the present specification can take the form of an entirely hardware embodiment, an entirely software embodiment or a combination of software and hardware.
  • one or more embodiments of the present specification can employ a computer program embodied on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer usable program code embodied therein.
  • the form of the product is not limited to disk storage, CD-ROM, optical storage, etc.
  • One or more embodiments of the present specification can be described in the general context of computer-executable instructions executed by a computer, such as a program module.
  • program modules include routines, programs, objects, components, data structures, and the like that perform particular tasks or implement particular abstract data types.
  • One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are connected through a communication network.
  • program modules can be located in both local and remote computer storage media including storage devices.

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Development Economics (AREA)
  • Multimedia (AREA)
  • Quality & Reliability (AREA)
  • Human Resources & Organizations (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Technology Law (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Game Theory and Decision Science (AREA)
  • Tourism & Hospitality (AREA)
  • Operations Research (AREA)
  • Educational Administration (AREA)
  • Traffic Control Systems (AREA)
  • Image Analysis (AREA)
  • Closed-Circuit Television Systems (AREA)
  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)

Abstract

一种车辆定损的方法、装置及设备，所述方法包括：采集包括待定损的目标车辆的标识的第一视频图像（S102），如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像（S104）；如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损（S106）。

Description

一种车辆定损的方法、装置及设备 技术领域
本说明书涉及计算机技术领域，尤其涉及一种车辆定损的方法、装置及设备。
背景技术
随着汽车工业的迅猛发展，汽车产销量、保有量越来越高。而随着汽车数量的迅速增长，道路的改善，特别是高速公路和立交桥的增多，汽车的车速增高，车辆发生交通事故导致的碰撞受损也日益增加，汽车查勘与定损、汽车保险与理赔行业也随之兴起。
当被保险的车辆发生交通事故时，保险机构首先需要做的就是到现场查勘定损，其中，车辆定损是根据车辆构造原理，通过科学、系统的专业化检查、测试与勘测手段，对车辆碰撞与事故现场进行综合分析，运用车辆估损资料与维修数据，对车辆碰撞修复进行科学系统的估损定价。车辆的定损涉及到维修、制造和车主等多方面的技术和利益，它是整个车险服务中矛盾比较突出的部分，因此，车辆定损边的非常重要，为了做好车辆的查勘与定损，保险机构会设置有车辆定损人员，当被保险的车辆发生交通事故时，保险机构会调度车辆定损人员到现场查勘定损。现今，保险机构对车辆定损人员的需求量越来越大，对车辆定损人员的要求也越来越规范。由于调度车辆定损人员到事故现场需要一定的时间，而且，如果保险机构的车辆定损人员不足，会使得到达现场所花费的时间更长，从而造成车辆定损效率低下，这样就需要提供更高效的车辆定损方案。
发明内容
本说明书实施例的目的是提供一种车辆定损的方法、装置及设备，以提供一种更高效的车辆定损方案。
为实现上述技术方案，本说明书实施例是这样实现的：
本说明书实施例提供的一种车辆定损的方法，所述方法包括：
采集包括待定损的目标车辆的标识的第一视频图像；
如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所 述目标车辆的损伤相关的第二视频图像；
如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
可选地，所述第二视频图像包括第三视频图像和第四视频图像，
所述继续采集包括所述目标车辆的损伤相关的第二视频图像，以及所述第二视频图像符合拍摄车辆损伤特征的预定要求，包括：
继续采集用于判定所述目标车辆的损伤部位的第三视频图像；
如果所述第三视频图像能够判定所述目标车辆的损伤部位，则继续采集用于判定所述目标车辆的损伤程度的第四视频图像；
如果所述第四视频图像能够判定所述目标车辆的损伤程度，则确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
可选地，所述第一视频图像符合拍摄标识的预定要求，包括：
从所述第一视频图像中提取与所述目标车辆的标识相关的图像特征；
如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
可选地，所述车辆标识的特征包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
可选地，所述如果所述第二视频图像符合拍摄车辆损伤特征的预定要求之前，所述方法还包括：
将所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器判断所述第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果；
接收所述定损服务器发送的所述判断结果；
所述如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损，包括：
如果所述判断结果指示所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
可选地，所述第一视频图像符合拍摄标识的预定要求，包括：
从所述第一视频图像中确定所述目标车辆的标识所在的第一区域；
通过预设的捕捉单元填充所述第一区域，得到捕捉单元组成的第二区域；
如果所述第二区域中的视频图像符合拍摄标识的预定要求，则将所述第二区域突出显示，以确定所述第一视频图像符合拍摄标识的预定要求。
可选地，所述第二视频图像符合拍摄车辆损伤特征的预定要求，包括：
从所述第二视频图像中确定所述目标车辆的损伤相关的第三区域；
通过预设的捕捉单元填充所述第三区域，得到捕捉单元组成的第四区域；
如果所述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将所述第四区域突出显示，以确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
可选地，所述基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损，包括：
将所述第一视频图像和所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器根据所述第一视频图像和所述第二视频图像对所述目标车辆进行定损，得到所述目标车辆的定损结果；
接收所述定损服务器发送的所述定损结果。
本说明书实施例提供的一种车辆定损的装置，所述装置包括：
第一视频采集模块，用于采集包括待定损的目标车辆的标识的第一视频图像；
第二视频采集模块，用于如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
车辆定损模块，用于如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
可选地，所述第二视频图像包括第三视频图像和第四视频图像，所述车辆定损模块，包括：
第三视频采集单元，用于继续采集用于判定所述目标车辆的损伤部位的第三视频图像；
第四视频采集单元，用于如果所述第三视频图像能够判定所述目标车辆的损伤部位，则继续采集用于判定所述目标车辆的损伤程度的第四视频 图像；
判定单元，用于如果所述第四视频图像能够判定所述目标车辆的损伤程度，则确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
可选地，所述第二视频采集模块，包括：
特征提取单元，用于从所述第一视频图像中提取与所述目标车辆的标识相关的图像特征；
判断单元，用于如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
可选地，所述车辆标识的特征包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
可选地，所述装置还包括：
视频图像发送模块，用于将所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器判断所述第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果；
判断结果接收模块，用于接收所述定损服务器发送的所述判断结果；
所述车辆定损模块，用于如果所述判断结果指示所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
可选地，所述第二视频采集模块，包括：
第一区域确定单元，用于从所述第一视频图像中确定所述目标车辆的标识所在的第一区域；
第一填充单元，用于通过预设的捕捉单元填充所述第一区域，得到捕捉单元组成的第二区域；
第一判定单元，用于如果所述第二区域中的视频图像符合拍摄标识的预定要求，则将所述第二区域突出显示，以确定所述第一视频图像符合拍摄标识的预定要求。
可选地，所述车辆定损模块，包括：
第三区域确定单元，用于从所述第二视频图像中确定所述目标车辆的损伤相关的第三区域；
第二填充单元，用于通过预设的捕捉单元填充所述第三区域，得到捕捉单元组成的第四区域；
第二判定单元，用于如果所述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将所述第四区域突出显示，以确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
可选地，所述车辆定损模块，包括：
视频图像发送单元，用于将所述第一视频图像和所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器根据所述第一视频图像和所述第二视频图像对所述目标车辆进行定损，得到所述目标车辆的定损结果；
定损结果接收单元，用于接收所述定损服务器发送的所述定损结果。
本说明书实施例提供的一种车辆定损的设备，所述车辆定损的设备包括：
处理器；以及
被安排成存储计算机可执行指令的存储器，所述可执行指令在被执行时使所述处理器：
采集包括待定损的目标车辆的标识的第一视频图像；
如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
由以上本说明书实施例提供的技术方案可见，本说明书实施例采集包括待定损的目标车辆的标识的第一视频图像，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损，这样，当用户仅需要通过摄像设备对待定损的目标车辆拍摄视频图像，即可完成对目标车辆的定损，不需要保险机构调度相应的车辆定损人员到现场进行查勘和定损，从而使得保险机构节省了大量人力资源和物力资源，而且，通过终端设备或服务器对用户上传的视频图像的分析进行车辆定损，节省了车辆定损所需的时间，提高了车辆定损的效率。
附图说明
为了更清楚地说明本说明书实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本说明书中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本说明书一种车辆定损的方法实施例；
图2A为本说明书一种车辆定损过程中视频拍摄界面的示意图；
图2B为本说明书一种车辆定损过程中开始拍摄视频图像时的视频拍摄界面示意图；
图2C为本说明书一种车辆定损过程中一个阶段的视频图像拍摄完成后进入下一步拍摄的视频拍摄界面示意图；
图2D为本说明书一种车辆定损过程中捕捉单元填充第一区域或第三区域的示意图；
图3为本说明书另一种车辆定损的方法实施例；
图4为本说明书又一种车辆定损的方法实施例；
图5为本说明书一种车辆定损的装置实施例；
图6为本说明书一种车辆定损的设备实施例。
具体实施方式
本说明书实施例提供一种车辆定损的方法、装置及设备。
为了使本技术领域的人员更好地理解本说明书中的技术方案，下面将结合本说明书实施例中的附图，对本说明书实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本说明书一部分实施例，而不是全部的实施例。基于本说明书中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都应当属于本说明书保护的范围。
实施例一
如图1所示，本说明书实施例提供一种车辆定损的方法，该方法的执行主体可以为终端设备，或者可以是由终端设备和服务器共同执行，其中，该终端设备可以如个人计算机等设备，也可以如手机、平板电脑等移动终端设备，该终端设备可以为用户使用的终端设备。该服务器可以是独立的 服务器，也可以是由多个服务器组成的服务器集群，而且，该服务器可以是进行车辆定损的服务器。该方法可以用于进行车辆定损等处理中。该方法具体可以包括以下步骤：
在步骤S102中，采集包括待定损的目标车辆的标识的第一视频图像。
其中，目标车辆可以是发生车辆碰撞后造成损伤的任意车辆。标识可以是用于确定目标车辆身份的信息，例如，目标车辆的车牌号码或目标车辆的发动机编号等。第一视频图像可以是通过摄像设备拍摄的视频的图像。
在实施中，进入21世纪以来，随着汽车工业的迅猛发展，汽车产销量、保有量越来越高。而随着汽车数量的迅速增长，道路的改善，特别是高速公路和立交桥的增多，汽车的车速增高，车辆发生交通事故导致的碰撞受损也日益增加，汽车查勘与定损、汽车保险与理赔行业也随之兴起。当被保险的车辆发生交通事故时，保险机构首先需要做的就是到现场查勘定损，其中，车辆定损可以是根据车辆构造原理，通过科学、系统的专业化检查、测试与勘测手段，对车辆碰撞与事故现场进行综合分析，运用车辆估损资料与维修数据，对车辆碰撞修复进行科学系统的估损定价。车辆的定损涉及到维修、制造和车主等多方面的技术和利益，它是整个车险服务中矛盾比较突出的部分。查勘和定损是为了确定事故损失而存在的，包括损失的真实性，损失的实际程度，维修或赔偿的程度等多个方面。为了做好车辆的查勘与定损，保险机构会设置有车辆定损人员，当被保险的车辆发生交通事故时，保险机构会调度车辆定损人员到现场查勘定损。现今，保险机构对车辆定损人员的需求量越来越大，对车辆定损人员的要求也越来越规范。由于调度车辆定损人员到事故现场需要一定的时间，而且，如果保险机构的车辆定损人员不足，会使得到达现场所花费的时间更长，从而造成时间的浪费和定损效率的低下，为此，本说明书实施例提供一种车辆的定损方法，即可以节省保险机构的人员的频繁调度，还可以提高车辆定损上午效率，具体可以包括以下内容：
考虑到当被保险的车辆(即目标车辆)发生交通事故时，报案人(如车辆驾驶员或乘车人等)到目标车辆的距离远远近于保险机构的车辆定损人员到目标车辆的距离，如果报案人能够上报目标车辆真实的、满足定损评判要求和定损所需要的规范证据等信息，则保险机构不需要再向目标车辆调度或派遣车辆定损人员，从而可以减少保险机构的人力资源的损耗， 而且还可以提高车辆定损的效率，因此，可设置一种车辆定损信息上报或上传的机制，通过该机制可以引导用户上报规范的车辆损伤信息，下面可以对该机制的一种可能的实现方式进行说明，具体如下：
首先，为了确保用户需要定损的目标车辆，可以引导用户上报目标车辆真实有效的身份信息，这样，可以避免车辆的定损欺诈，尽可能的降低可能存在的风险。本说明书实施例中，为了尽可能的降低风险，可以采用视频图像的方式上报车辆定损相关的信息。用户的终端设备中可以设置有车辆定损信息上报机制的触发按键，另外，还可以基于车辆定损信息上报机制，通过计算机编程语言编写相应的应用程序。当用户需要向保险机构上报车辆的损伤情况时，可以点击车辆定损信息上报机制的触发按键，或者，启动相应的应用程序，以触发执行车辆定损信息上报机制。终端设备可以执行该车辆定损信息上报机制，此时，如图2A所示，终端设备可以启动摄像头，并打开视频拍摄功能，通过摄像头拍摄视频图像，此时，终端设备的显示界面中可以设置相应的提示信息，通过上述提示信息，用户可以执行相应的操作，其中，该提示信息可以用于提示用户拍摄目标车辆的标识等，这样，终端设备可以采集包括待定损的目标车辆的标识的第一视频图像。例如，该提示信息提示用户拍摄目标车辆的车牌号码，这样，如图2A和图2B所示，用户可以将终端设备的摄像头对准目标车辆的车牌号码进行视频拍摄，得到第一视频图像，其中，在实际应用中，如果标识为车牌号码，则终端设备的摄像预览界面中可以提供一个矩形区域，在拍摄车牌号码时，可以提示用户将车牌号码的图像放置在上述矩形区域内，以方便后续对车牌号码的识别。
在步骤S104中，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像。
其中，第二视频图像可以是通过摄像设备拍摄的、其中包括目标车辆损伤情况的视频的图像，其中的目标车辆损伤情况可以包括损伤部位和损伤程度等。拍摄标识的预定要求可以根据实际情况设定，例如，标识为车牌号码，则拍摄标识的预定要求可以为车牌号码的特征，可以包括：相对规则的矩形(其中，在非平面拍摄时为平行四边形)、蓝底白字或黄底黑字、中文+白点+5位英文和/或数字的组合等。
在实施中，用户在使用终端设备拍摄目标车辆标识的过程中，终端设 备可以对拍摄的第一视频图像进行图像分析，即可以实时计算视频窗口中，所拍摄目标车辆的目标区域，通过捕捉显示单元的组合，填充目标区域的面积，从而可以捕捉到第一视频图像中存在的与标识相对应的特征，然后，可以锁定相应的区域，并对该区域进行进一步识别判断，从而确定第一视频图像是否符合拍摄标识的预定要求。
例如，标识为车牌号码，终端设备可以对拍摄的第一视频图像进行图像分析，即可以实时计算视频窗口中所拍摄目标车辆的与车牌号码的“相对规则的矩形”相匹配的目标区域，通过捕捉显示单元的组合，填充目标区域的面积，从而可以捕捉到第一视频图像中存在的与车牌号码的“相对规则的矩形”相匹配的特征，然后，可以锁定上述规则的矩形区域，并对该规则的矩形区域进行进一步识别，即判断该规则的矩形区域是否是蓝底白字或黄底黑字，以及判断该规则的矩形区域中是否包含中文+白点+5位英文和/或数字的组合等，从而确定第一视频图像是否符合拍摄标识的预定要求。如果该规则的矩形区域是蓝底白字或黄底黑字，且其中包含中文+白点+5位英文和/或数字的组合，则确定第一视频图像符合拍摄标识的预定要求，否则，第一视频图像不符合拍摄标识的预定要求。其中，第一视频图像是否符合拍摄标识的预定要求的直观处理方法可以包括多种，例如对目标区域进行变色处理，即如果确定第一视频图像符合拍摄标识的预定要求，则可以将上述规则的矩形区域由灰色变为红色等，从而使得用户及时了解拍摄的视频图像是否符合规范或要求。
如果第一视频图像符合拍摄标识的预定要求，则终端设备可以开启下一步引导的提示信息，此时，如图2C所示，终端设备的显示界面中可以设置下一步的提示信息，通过上述提示信息，用户可以继续拍摄相应的视频图像，其中，该提示信息可以用于提示用户拍摄目标车辆的损伤情况等，这样，终端设备可以采集包括目标车辆的损伤部位和损伤程度的第二视频图像。
在步骤S106中，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损。
其中，拍摄车辆损伤特征的预定要求可以根据实际情况设定，例如，标识为车牌号码，则拍摄标识的预定要求可以为车牌号码的特征，可以包括：相对规则的矩形(其中，在非平面拍摄时为平行四边形)、蓝底白字或 黄底黑字、中文+白点+5位英文和/或数字的组合等。
在实施中，用户在使用终端设备拍摄包括目标车辆的损伤相关的第二视频图像的过程中，终端设备可以对拍摄的第二视频图像进行图像分析，即可以实时计算视频窗口中所拍摄目标车辆的目标区域，通过捕捉显示单元的组合，填充目标区域的面积，从而可以捕捉到第二视频图像中存在的车辆损伤特征，然后，可以锁定相应的区域，并对该区域进行进一步识别判断，从而确定第二视频图像是否符合拍摄车辆损伤特征的预定要求。其中，第二视频图像是否符合拍摄车辆损伤特征的预定要求的直观处理方法可以包括多种，例如对目标区域进行变色处理等。
如果第二视频图像符合拍摄车辆损伤特征的预定要求，则终端设备可以提示用户已完成本次拍摄，如果用户指示继续拍摄，则可以继续通过上述步骤S104和步骤S106的处理进行视频图像拍摄，如果用户指示结束拍摄，则终端设备可以获取第一视频图像和第二视频图像，并可以分别对第一视频图像和第二视频图像进行图像分析，确定目标车辆损伤的所属部件、损伤程度，从而制定维修方案、维修价格以及车险的理赔建议等，从而达到对目标车辆进行定损的目的。
需要说明的是，对目标车辆进行定损的处理可以是在终端设备中执行，也可以是由服务器执行。对于由服务器执行的情况，终端设备获取到第一视频图像和第二视频图像后，可以将第一视频图像和第二视频图像发送给车辆定损服务器，车辆定损服务器接收到第一视频图像和第二视频图像后，可以对第一视频图像和第二视频图像进行视频分析，确定目标车辆损伤的所属部件、损伤程度，从而制定维修方案、维修价格以及车险的理赔建议等车辆定损结果，然后，可以将车辆定损结果发送给终端设备，这样，可以减轻终端设备的数据处理压力，提高数据处理效率。
本说明书实施例提供一种车辆定损的方法，采集包括待定损的目标车辆的标识的第一视频图像，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损，这样，当用户仅需要通过摄像设备对待定损的目标车辆拍摄视频图像，即可完成对目标车辆的定损，不需要保险机构调度相应的车辆定损人员到现场进行查勘和定损，从而使得保险机构节省了大量 人力资源和物力资源，而且，通过终端设备或服务器对用户上传的视频图像的分析进行车辆定损，节省了车辆定损所需的时间，提高了车辆定损的效率。
实施例二
如图3所示，本说明书实施例提供一种车辆定损的方法，该方法的执行主体可以为终端设备，其中，该终端设备可以如个人计算机等设备，也可以如手机、平板电脑等移动终端设备，该终端设备可以为用户使用的终端设备。该方法可以用于进行车辆定损等处理中。该方法具体可以包括以下步骤：
在步骤S302中，采集包括待定损的目标车辆的标识的第一视频图像。
其中，车辆标识的特征可以包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口等，在实际应用中，车辆标识的特征也并不限于上述内容，还可以包括能够证明目标车辆身份的其它信息，例如发动机编号或车辆识别代码(VIN，Vehicle Identification Number)等。
上述步骤S302的步骤内容与上述实施例一中步骤S102的步骤内容相同，步骤S302的具体处理过程可以参见上述实施例一中步骤S102的相关内容，在此不再赘述。
在步骤S304中，从第一视频图像中提取与目标车辆的标识相关的图像特征。
在实施中，终端设备中可以设置有视频图像的特征提取算法，该特征提取算法可以对视频图像中属于特征性的信息进行提取。终端设备通过上述步骤S302的处理过程获取第一视频图像后，可以调取预先设置的特征提取算法，通过特征提取算法可以对第一视频图像进行分析，可以从第一视频图像中提取包含特征性的信息，并可以根据目标车辆的标识的相关信息，可以从提取的包含特征性的信息中提取与目标车辆的标识相关的图像特征。
在步骤S306中，如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
在实施中，终端设备中可以存储有车辆的特征库，该特征库中可以存储有车辆标识的特征，具体地，该特征库中可以存储有车牌的相关特征、 前大灯的相关特征、轮毂的相关特征、车门把手的相关特征、车辆尾灯的相关特征、车辆后视镜的相关特征、油箱盖的相关特征和充电口的相关特征等，其中，车牌的相关特征可以包括：相对规则的矩形(其中，在非平面拍摄时为平行四边形)、蓝底白字或黄底黑字、中文+白点+5位英文和/或数字的组合或多位英文和数字的组合等，前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖或充电口的相关特征可以包括：外观样式特征、内部结构样式特征等。
终端设备通过上述步骤S304的处理提取到第一视频图像的图像特征后，可以将提取的图像特征与特征库中存储的车辆标识的特征进行匹配，如果提取的图像特征与特征库中存储的车辆标识的特征不匹配，则表明用户拍摄的第一视频图像不符合规范或要求，此时，可以输出提示信息以提示用户重新拍摄视频图像，如果提取的图像特征与特征库中存储的车辆标识的特征相匹配，则表明用户拍摄的第一视频图像符合规范或要求，此时，可以存储该第一视频图像。
在实际应用中，上述确定第一视频图像是否符合拍摄标识的预定要求的处理，可以通过多种方式实现，以下提供一种可选的处理方式，具体可以包括以下步骤一～步骤三。
步骤一，从上述第一视频图像中确定目标车辆的标识所在的第一区域。
在实施中，可以通过目标车辆的标识的相关特征确定第一区域，目标车辆的标识可以参见上述相关内容，例如，目标车辆的标识为车牌号码，则第一区域可以是车牌号码所在的车牌的区域，车牌的相关特征可以参见上述相关内容，即车牌的相关特征可以包括：相对规则的矩形、蓝底白字或黄底黑字、中文+白点+5位英文和/或数字的组合或多位英文和数字的组合等，因此，可以在第一视频图像中查找具备上述特征的区域，可以将上述区域确定为第一区域，该第一区域中会包括目标车辆的标识。
步骤二，通过预设的捕捉单元填充上述第一区域，得到捕捉单元组成的第二区域。
其中，预设的捕捉单元可以是图像捕捉的基本组成单元，捕捉单元的大小可以根据实际情况设定，例如，捕捉单元可以是一个方形，该方形的边长可以为1毫米或一个或多个像素点的长度等。
在实施中，通过上述步骤一的处理，可以实时计算视频窗口中所拍摄 的目标车辆中存在目标车辆的标识的相关特征的第一区域，并可以确定第一区域的形状，然后，如图2D所示，可以使用捕捉单元，根据第一区域的形状对第一区域所圈定的区域面积进行填充，直到通过多个捕捉单元填充的区域覆盖第一区域为止，其中，多个捕捉单元中的任何两个捕捉单元之间不存在重叠放置的情况。最终，可以得到捕捉单元组成的第二区域。
步骤三，如果上述第二区域中的视频图像符合拍摄标识的预定要求，则将该第二区域突出显示，以确定第一视频图像符合拍摄标识的预定要求。
在实施中，可以通过上述步骤S304的处理提取第二区域中的视频图像的图像特征后，可以将提取的图像特征与特征库中存储的车辆标识的特征进行匹配，如果提取的图像特征与特征库中存储的车辆标识的特征不匹配，则表明用户拍摄的第一视频图像不符合规范或要求，此时，可以输出提示信息以提示用户重新拍摄视频图像，如果提取的图像特征与特征库中存储的车辆标识的特征相匹配，则此时，为了能够让用户及时了解其拍摄的视频图像符合要求，可以将该第二区域突出显示，以表明用户拍摄的第一视频图像符合规范或要求。其中，将该第二区域突出显示的具体实现方式可以包括多种，例如，可以第二区域的颜色变换为与之前的颜色不同的颜色，如由蓝色变为红色等，或者，也可以将第二区域进行闪烁显示等。
如图2C所示，通过上述方式确定目标车辆的身份后，可以通过如由不可操作按键或箭头变为可操作按键或箭头，或者，直接解锁下一步处理等方式引导用户进入下一步的处理，即请求用户拍摄车辆损伤情况的相关视频图像，考虑到确定车辆损伤情况往往包括两个部分，即确定车辆损伤的部位和确定损伤的程度，为此，可以通过以下步骤S308和步骤S310的处理确定目标车辆的损伤情况。
在步骤S308中，继续采集用于判定目标车辆的损伤部位的第三视频图像。
在实施中，终端设备中可以显示指示用户对准车辆损伤的部位进行视频拍摄的指示信息，用户可以根据指示信息的内容，将终端设备的摄像头对准目标车辆的损伤部位，继续进行视频拍摄。用户在实时拍摄目标车辆的损伤部位的第三视频图像时，终端设备可以实时计算视频窗口中所拍摄的目标车辆中存在损伤部位的目标区域，然后，可以通过捕捉显示单元的组合，填充目标区域的面积，从而可以捕捉到目标车辆完整的损伤部位的 第三视频图像，可以锁定上述目标区域。
在步骤S310中，如果第三视频图像能够判定目标车辆的损伤部位，则继续采集用于判定目标车辆的损伤程度的第四视频图像。
在实施中，终端设备通过上述步骤S308的处理得到包括目标车辆的损伤部位的第三视频图像后，可以对该第三视频图像进行分析，可以从第三视频图像中提取包含特征性的信息，并可以根据目标车辆的各个部位的相关信息，可以从提取的包含特征性的信息中提取与判定目标车辆的损伤部位相关的图像特征，并可以通过提取的图像特征判定目标车辆的损伤部位，如果终端设备能够通过提取的图像特征判别出损伤部位属于目标车辆的哪个位置，则可以通过如由不可操作按键或箭头变为可操作按键或箭头，或者，直接解锁下一步处理等方式引导用户进入下一步的处理，即请求用户拍摄车辆程度的相关视频图像。此时，终端设备中可以显示指示用户对准车辆损伤的部位进行损伤细节拍摄的指示信息，用户可以根据指示信息的内容，将终端设备的摄像头对准目标车辆的损伤部位，继续进行详细的视频拍摄。用户在实时拍摄目标车辆的损伤程度的第四视频图像时，终端设备可以实时计算视频窗口中所拍摄的目标车辆中存在损伤部位的损伤程度的目标区域，然后，可以通过捕捉显示单元的组合，填充目标区域的面积，从而可以捕捉到目标车辆损伤程度的第四视频图像。
在步骤S312中，如果第四视频图像能够判定目标车辆的损伤程度，则基于第一视频图像和第二视频图像，对目标车辆进行定损。
其中，第二视频图像可以包括第三视频图像和第四视频图像。
在实施中，终端设备通过上述步骤S310的处理得到包括目标车辆的损伤程度的第四视频图像后，可以对该第四视频图像进行分析，可以从第四视频图像中提取包含特征性的信息，并可以根据目标车辆的各个部位的相关信息，可以从提取的包含特征性的信息中提取与判定目标车辆的损伤程度相关的图像特征，并可以通过提取的图像特征判定目标车辆的损伤程度，如果终端设备能够通过提取的图像特征判别出损伤部位的损伤程度，则可以基于第一视频图像和第二视频图像，对目标车辆进行定损，对于上述对车辆进行定损的处理过程可以参见上述实施例一中步骤S106的相关内容，在此不再赘述。
在实际应用中，上述确定第二视频图像是否拍摄车辆损伤特征的预定 要求的处理，可以通过多种方式实现，以下提供一种可选的处理方式，如图2D所示，具体可以包括以下步骤一～步骤三。
步骤一，从上述第二视频图像中确定目标车辆的损伤相关的第三区域。
步骤二，通过预设的捕捉单元填充上述第三区域，得到捕捉单元组成的第四区域。
步骤三，如果上述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将该第四区域突出显示，以确定上述第二视频图像符合拍摄车辆损伤特征的预定要求。
上述步骤一～步骤三的具体处理过程可以参见上述相关内容，在此不再赘述。其中，需要说明的是，对于第二视频图像包括第三视频图像和第四视频图像的情况，其中，第三视频图像能够判定目标车辆的损伤部位的处理，基于上述步骤一～步骤三，则有：从第三视频图像中确定目标车辆的损伤部位所在的第一子区域；通过预设的捕捉单元填充上述第一子区域，得到捕捉单元组成的第二子区域；如果上述第二子区域中的视频图像能够判定目标车辆的损伤部位，则将该第二子区域突出显示，以确定上述第三视频图像能够判定目标车辆的损伤部位。其中，第四视频图像能够判定目标车辆的损伤程度的处理，基于上述步骤一～步骤三，则有：从第四视频图像中确定目标车辆的损伤程度的第三子区域；通过预设的捕捉单元填充上述第三子区域，得到捕捉单元组成的第四子区域；如果上述第四子区域中的视频图像能够判定目标车辆的损伤程度，则将该第四子区域突出显示，以确定上述第四视频图像能够判定目标车辆的损伤部位。其中，第三区域可以包括第一子区域和第三子区域，第四区域可以包括第二子区域和第四子区域。
需要说明的是，上述第二视频图像是否符合拍摄车辆损伤特征的预定要求的处理是通过终端设备实现的，在实际应用中，为了降低终端设备的处理压力，可以将判断第二视频图像是否符合拍摄车辆损伤特征的预定要求的处理交由服务器完成，则相应的处理可以包括以下步骤一和步骤二：
步骤一，将第二视频图像发送给车辆定损服务器，以使车辆定损服务器判断第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果。
在实施中，基于上述第二视频图像包括第三视频图像和第四视频图像 的情况，上述步骤一的具体处理过程还可以包括以下内容：如果第一视频图像符合拍摄标识的预定要求，则继续采集用于判定目标车辆的损伤部位的第三视频图像；将第三视频图像发送给车辆定损服务器，以使车辆定损服务器判断第三视频图像是否能够判定目标车辆的损伤部位，得到判断结果，车辆定损服务器可以向终端设备发送该判断结果。如果该判断结果指示第三视频图像能够判定目标车辆的损伤部位，则终端设备继续采集用于判定目标车辆的损伤程度的第四视频图像，可以将第四视频图像发送给车辆定损服务器，以使车辆定损服务器判断第四视频图像是否能够判定目标车辆的损伤程度，得到判断结果，车辆定损服务器可以向终端设备发送该判断结果。其中，具体判断第三视频图像是否能够判定目标车辆的损伤部位，以及第四视频图像是否能够判定目标车辆的损伤程度的处理过程，可以参见上述相关内容，在此不再赘述。
步骤二，接收定损服务器发送的上述判断结果。
基于上述步骤一和步骤二的处理过程，上述步骤S312的处理可以为：如果上述判断结果指示第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损。
本说明书实施例提供一种车辆定损的方法，采集包括待定损的目标车辆的标识的第一视频图像，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损，这样，当用户仅需要通过摄像设备对待定损的目标车辆拍摄视频图像，即可完成对目标车辆的定损，不需要保险机构调度相应的车辆定损人员到现场进行查勘和定损，从而使得保险机构节省了大量人力资源和物力资源，而且，通过终端设备或服务器对用户上传的视频图像的分析进行车辆定损，节省了车辆定损所需的时间，提高了车辆定损的效率。
实施例三
如图4所示，本说明书实施例提供一种车辆定损的方法，该方法的执行主体可以为终端设备和车辆定损服务器，其中，该终端设备可以如个人计算机等设备，也可以如手机、平板电脑等移动终端设备，该终端设备可 以为用户使用的终端设备。该车辆定损服务器可以是独立的服务器，也可以是由多个服务器组成的服务器集群，而且，该车辆定损服务器可以是进行车辆定损的服务器。该方法可以用于进行车辆定损等处理中。该方法具体可以包括以下步骤：
在步骤S402中，终端设备采集包括待定损的目标车辆的标识的第一视频图像。
其中，车辆标识的特征可以包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
在步骤S404中，终端设备从第一视频图像中提取与目标车辆的标识相关的图像特征。
在步骤S406中，如果提取的图像特征与设定的车辆标识的特征相匹配，则终端设备确定第一视频图像符合拍摄标识的预定要求。
上述步骤S402～步骤S406的处理过程可以参见上述实施例二中步骤S302～步骤S306的相关内容，在此不再赘述。
在步骤S408中，终端设备继续采集用于判定目标车辆的损伤部位的第三视频图像。
在步骤S410中，如果第三视频图像能够判定目标车辆的损伤部位，则终端设备继续采集用于判定目标车辆的损伤程度的第四视频图像。
上述步骤S408和步骤S410的处理过程可以参见上述实施例二中步骤S308和步骤S310的相关内容，在此不再赘述。
为了减轻终端设备的处理压力，可以将撤离定损的处理交由服务器(即车辆定损服务器)完成，具体额可以参见下述步骤S412～步骤S416的处理。
在步骤S412中，如果第四视频图像能够判定目标车辆的损伤程度，则终端设备将第一视频图像和第二视频图像发送给车辆定损服务器，其中，第二视频图像包括第三视频图像和第四视频图像。
需要说明的是，上述第二视频图像是否符合拍摄车辆损伤特征的预定要求的处理是通过终端设备实现的，在实际应用中，为了降低终端设备的处理压力，可以将判断第二视频图像是否符合拍摄车辆损伤特征的预定要求的处理交由服务器完成，则相应的处理可以包括以下步骤一和步骤二：
步骤一，将第二视频图像发送给车辆定损服务器，以使车辆定损服务器判断第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结 果。
在实施中，基于上述第二视频图像包括第三视频图像和第四视频图像的情况，上述步骤一的具体处理过程还可以包括以下内容：如果第一视频图像符合拍摄标识的预定要求，则继续采集用于判定目标车辆的损伤部位的第三视频图像；将第三视频图像发送给车辆定损服务器，以使车辆定损服务器判断第三视频图像是否能够判定目标车辆的损伤部位，得到判断结果，车辆定损服务器可以向终端设备发送该判断结果。如果该判断结果指示第三视频图像能够判定目标车辆的损伤部位，则终端设备继续采集用于判定目标车辆的损伤程度的第四视频图像，可以将第四视频图像发送给车辆定损服务器，以使车辆定损服务器判断第四视频图像是否能够判定目标车辆的损伤程度，得到判断结果，车辆定损服务器可以向终端设备发送该判断结果。
步骤二，接收定损服务器发送的上述判断结果。
基于上述步骤一和步骤二的处理过程，上述步骤S412的处理可以为：如果上述判断结果指示第二视频图像符合拍摄车辆损伤特征的预定要求，则终端设备将第一视频图像和第二视频图像发送给车辆定损服务器。
在步骤S414中，车辆定损服务器根据第一视频图像和第二视频图像对目标车辆进行定损，得到目标车辆的定损结果。
在实施中，车辆定损服务器接收到第一视频图像和第二视频图像(包括第三视频图像和第四视频图像)后，可以对第一视频图像和第二视频图像分别进行视频分析，确定目标车辆损伤的所属部件、损伤程度，从而制定维修方案、维修价格以及车险的理赔建议等车辆定损结果，这样，可以提高车辆定损的处理效率。
在步骤S416中，终端设备接收定损服务器发送的上述定损结果。
本说明书实施例提供一种车辆定损的方法，采集包括待定损的目标车辆的标识的第一视频图像，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损，这样，当用户仅需要通过摄像设备对待定损的目标车辆拍摄视频图像，即可完成对目标车辆的定损，不需要保险机构调度相应的车辆定损人员到现场进行查勘和定损，从而使得保险机构节省了大量 人力资源和物力资源，而且，通过终端设备或服务器对用户上传的视频图像的分析进行车辆定损，节省了车辆定损所需的时间，提高了车辆定损的效率。
实施例四
以上为本说明书实施例提供的车辆定损的方法，基于同样的思路，本说明书实施例还提供一种车辆定损的装置，如图5所示。
该车辆定损的装置包括：第一视频采集模块501、第二视频采集模块502和车辆定损模块503，其中：
第一视频采集模块501，用于采集包括待定损的目标车辆的标识的第一视频图像；
第二视频采集模块502，用于如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
车辆定损模块503，用于如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
本说明书实施例中，所述第二视频图像包括第三视频图像和第四视频图像，所述车辆定损模块503，包括：
第三视频采集单元，用于继续采集用于判定所述目标车辆的损伤部位的第三视频图像；
第四视频采集单元，用于如果所述第三视频图像能够判定所述目标车辆的损伤部位，则继续采集用于判定所述目标车辆的损伤程度的第四视频图像；
判定单元，用于如果所述第四视频图像能够判定所述目标车辆的损伤程度，则确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
本说明书实施例中，所述第二视频采集模块502，包括：
特征提取单元，用于从所述第一视频图像中提取与所述目标车辆的标识相关的图像特征；
判断单元，用于如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
本说明书实施例中，所述车辆标识的特征包括以下一个或多个的组合： 车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
本说明书实施例中，所述装置还包括：
视频图像发送模块，用于将所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器判断所述第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果；
判断结果接收模块，用于接收所述定损服务器发送的所述判断结果；
所述车辆定损模块，用于如果所述判断结果指示所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
本说明书实施例中，所述第二视频采集模块502，包括：
第一区域确定单元，用于从所述第一视频图像中确定所述目标车辆的标识所在的第一区域；
第一填充单元，用于通过预设的捕捉单元填充所述第一区域，得到捕捉单元组成的第二区域；
第一判定单元，用于如果所述第二区域中的视频图像符合拍摄标识的预定要求，则将所述第二区域突出显示，以确定所述第一视频图像符合拍摄标识的预定要求。
本说明书实施例中，所述车辆定损模块503，包括：
第三区域确定单元，用于从所述第二视频图像中确定所述目标车辆的损伤相关的第三区域；
第二填充单元，用于通过预设的捕捉单元填充所述第三区域，得到捕捉单元组成的第四区域；
第二判定单元，用于如果所述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将所述第四区域突出显示，以确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
本说明书实施例中，所述车辆定损模块503，包括：
视频图像发送单元，用于将所述第一视频图像和所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器根据所述第一视频图像和所述第二视频图像对所述目标车辆进行定损，得到所述目标车辆的定损结果；
定损结果接收单元，用于接收所述定损服务器发送的所述定损结果。
本说明书实施例提供一种车辆定损的装置，采集包括待定损的目标车辆的标识的第一视频图像，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损，这样，当用户仅需要通过摄像设备对待定损的目标车辆拍摄视频图像，即可完成对目标车辆的定损，不需要保险机构调度相应的车辆定损人员到现场进行查勘和定损，从而使得保险机构节省了大量人力资源和物力资源，而且，通过终端设备或服务器对用户上传的视频图像的分析进行车辆定损，节省了车辆定损所需的时间，提高了车辆定损的效率。
实施例五
以上为本说明书实施例提供的车辆定损的装置，基于同样的思路，本说明书实施例还提供一种车辆定损的设备，如图6所示。
所述车辆定损的设备可以为上述实施例提供的终端设备。
车辆定损的设备可因配置或性能不同而产生比较大的差异，可以包括一个或一个以上的处理器601和存储器602，存储器602中可以存储有一个或一个以上存储应用程序或数据。其中，存储器602可以是短暂存储或持久存储。存储在存储器602的应用程序可以包括一个或一个以上模块(图示未示出)，每个模块可以包括对车辆定损的设备中的一系列计算机可执行指令。更进一步地，处理器601可以设置为与存储器602通信，在车辆定损的设备上执行存储器602中的一系列计算机可执行指令。车辆定损的设备还可以包括一个或一个以上电源603，一个或一个以上有线或无线网络接口604，一个或一个以上输入输出接口605，一个或一个以上键盘606。
具体在本实施例中，车辆定损的设备包括有存储器，以及一个或一个以上的程序，其中一个或者一个以上程序存储于存储器中，且一个或者一个以上程序可以包括一个或一个以上模块，且每个模块可以包括对车辆定损的设备中的一系列计算机可执行指令，且经配置以由一个或者一个以上处理器执行该一个或者一个以上程序包含用于进行以下计算机可执行指令：
采集包括待定损的目标车辆的标识的第一视频图像；
如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
本说明书实施例中，所述第二视频图像包括第三视频图像和第四视频图像，
所述继续采集包括所述目标车辆的损伤相关的第二视频图像，以及所述第二视频图像符合拍摄车辆损伤特征的预定要求，包括：
继续采集用于判定所述目标车辆的损伤部位的第三视频图像；
如果所述第三视频图像能够判定所述目标车辆的损伤部位，则继续采集用于判定所述目标车辆的损伤程度的第四视频图像；
如果所述第四视频图像能够判定所述目标车辆的损伤程度，则确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
本说明书实施例中，所述第一视频图像符合拍摄标识的预定要求，包括：
从所述第一视频图像中提取与所述目标车辆的标识相关的图像特征；
如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
本说明书实施例中，所述车辆标识的特征包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
本说明书实施例中，所述如果所述第二视频图像符合拍摄车辆损伤特征的预定要求之前，还包括：
将所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器判断所述第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果；
接收所述定损服务器发送的所述判断结果；
所述如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损，包括：
如果所述判断结果指示所述第二视频图像符合拍摄车辆损伤特征的预 定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
本说明书实施例中，所述第一视频图像符合拍摄标识的预定要求，包括：
从所述第一视频图像中确定所述目标车辆的标识所在的第一区域；
通过预设的捕捉单元填充所述第一区域，得到捕捉单元组成的第二区域；
如果所述第二区域中的视频图像符合拍摄标识的预定要求，则将所述第二区域突出显示，以确定所述第一视频图像符合拍摄标识的预定要求。
本说明书实施例中，所述第二视频图像符合拍摄车辆损伤特征的预定要求，包括：
从所述第二视频图像中确定所述目标车辆的损伤相关的第三区域；
通过预设的捕捉单元填充所述第三区域，得到捕捉单元组成的第四区域；
如果所述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将所述第四区域突出显示，以确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
本说明书实施例中，所述基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损，包括：
将所述第一视频图像和所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器根据所述第一视频图像和所述第二视频图像对所述目标车辆进行定损，得到所述目标车辆的定损结果；
接收所述定损服务器发送的所述定损结果。
本说明书实施例提供一种车辆定损的设备，采集包括待定损的目标车辆的标识的第一视频图像，如果第一视频图像符合拍摄标识的预定要求，则继续采集包括目标车辆的损伤相关的第二视频图像，如果第二视频图像符合拍摄车辆损伤特征的预定要求，则基于第一视频图像和第二视频图像，对目标车辆进行定损，这样，当用户仅需要通过摄像设备对待定损的目标车辆拍摄视频图像，即可完成对目标车辆的定损，不需要保险机构调度相应的车辆定损人员到现场进行查勘和定损，从而使得保险机构节省了大量 人力资源和物力资源，而且，通过终端设备或服务器对用户上传的视频图像的分析进行车辆定损，节省了车辆定损所需的时间，提高了车辆定损的效率。
上述对本说明书特定实施例进行了描述。其它实施例在所附权利要求书的范围内。在一些情况下，在权利要求书中记载的动作或步骤可以按照不同于实施例中的顺序来执行并且仍然可以实现期望的结果。另外，在附图中描绘的过程不一定要求示出的特定顺序或者连续顺序才能实现期望的结果。在某些实施方式中，多任务处理和并行处理也是可以的或者可能是有利的。
在20世纪90年代，对于一个技术的改进可以很明显地区分是硬件上的改进(例如，对二极管、晶体管、开关等电路结构的改进)还是软件上的改进(对于方法流程的改进)。然而，随着技术的发展，当今的很多方法流程的改进已经可以视为硬件电路结构的直接改进。设计人员几乎都通过将改进的方法流程编程到硬件电路中来得到相应的硬件电路结构。因此，不能说一个方法流程的改进就不能用硬件实体模块来实现。例如，可编程逻辑器件(Programmable Logic Device，PLD)(例如现场可编程门阵列(Field Programmable Gate Array，FPGA))就是这样一种集成电路，其逻辑功能由用户对器件编程来确定。由设计人员自行编程来把一个数字系统“集成”在一片PLD上，而不需要请芯片制造厂商来设计和制作专用的集成电路芯片。而且，如今，取代手工地制作集成电路芯片，这种编程也多半改用“逻辑编译器(logic compiler)”软件来实现，它与程序开发撰写时所用的软件编译器相类似，而要编译之前的原始代码也得用特定的编程语言来撰写，此称之为硬件描述语言(Hardware Description Language，HDL)，而HDL也并非仅有一种，而是有许多种，如ABEL(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby Hardware Description Language)等，目前最普遍使用的是VHDL(Very-High-Speed Integrated Circuit Hardware Description Language)与Verilog。本领域技术人员也应该清楚，只需要将方法流程用上述几种硬件描述语言稍作逻辑编程并编程到集成电路中，就可以很容易得到实现该逻 辑方法流程的硬件电路。
控制器可以按任何适当的方式实现，例如，控制器可以采取例如微处理器或处理器以及存储可由该(微)处理器执行的计算机可读程序代码(例如软件或固件)的计算机可读介质、逻辑门、开关、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程逻辑控制器和嵌入微控制器的形式，控制器的例子包括但不限于以下微控制器：ARC 625D、Atmel AT91SAM、Microchip PIC18F26K20以及Silicone Labs C8051F320，存储器控制器还可以被实现为存储器的控制逻辑的一部分。本领域技术人员也知道，除了以纯计算机可读程序代码方式实现控制器以外，完全可以通过将方法步骤进行逻辑编程来使得控制器以逻辑门、开关、专用集成电路、可编程逻辑控制器和嵌入微控制器等的形式来实现相同功能。因此这种控制器可以被认为是一种硬件部件，而对其内包括的用于实现各种功能的装置也可以视为硬件部件内的结构。或者甚至，可以将用于实现各种功能的装置视为既可以是实现方法的软件模块又可以是硬件部件内的结构。
上述实施例阐明的系统、装置、模块或单元，具体可以由计算机芯片或实体实现，或者由具有某种功能的产品来实现。一种典型的实现设备为计算机。具体的，计算机例如可以为个人计算机、膝上型计算机、蜂窝电话、相机电话、智能电话、个人数字助理、媒体播放器、导航设备、电子邮件设备、游戏控制台、平板计算机、可穿戴设备或者这些设备中的任何设备的组合。
为了描述的方便，描述以上装置时以功能分为各种单元分别描述。当然，在实施本说明书一个或多个实施例时可以把各单元的功能在同一个或多个软件和/或硬件中实现。
本领域内的技术人员应明白，本说明书的实施例可提供为方法、系统、或计算机程序产品。因此，本说明书一个或多个实施例可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本说明书一个或多个实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本说明书的实施例是参照根据本说明书实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程 序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本说明书的实施例可提供为方法、系统或计算机程序产品。因此，本说明书一个或多个实施例可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本说明书一个或多个实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本说明书一个或多个实施例可以在由计算机执行的计算机可执行指令的一般上下文中描述，例如程序模块。一般地，程序模块包括执行特定任务或实现特定抽象数据类型的例程、程序、对象、组件、数据结构等等。也可以在分布式计算环境中实践本说明书一个或多个实施例，在这些分布式计算环境中，由通过通信网络而被连接的远程处理设备来执行任务。在分布式计算环境中，程序模块可以位于包括存储设备在内的本地和远程计算机存储介质中。
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于系统实施例而言，由于其基本相似于方法实施例，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
以上所述仅为本说明书的实施例而已，并不用于限制本说明书。对于本领域技术人员来说，本说明书可以有各种更改和变化。凡在本说明书的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本说明书的权利要求范围之内。

Claims (17)

  1. 一种车辆定损的方法，所述方法包括：
    采集包括待定损的目标车辆的标识的第一视频图像；
    如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
    如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
  2. 根据权利要求1所述的方法，所述第二视频图像包括第三视频图像和第四视频图像，
    所述继续采集包括所述目标车辆的损伤相关的第二视频图像，以及所述第二视频图像符合拍摄车辆损伤特征的预定要求，包括：
    继续采集用于判定所述目标车辆的损伤部位的第三视频图像；
    如果所述第三视频图像能够判定所述目标车辆的损伤部位，则继续采集用于判定所述目标车辆的损伤程度的第四视频图像；
    如果所述第四视频图像能够判定所述目标车辆的损伤程度，则确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
  3. 根据权利要求2所述的方法，所述第一视频图像符合拍摄标识的预定要求，包括：
    从所述第一视频图像中提取与所述目标车辆的标识相关的图像特征；
    如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
  4. 根据权利要求3所述的方法，所述车辆标识的特征包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
  5. 根据权利要求4所述的方法，所述如果所述第二视频图像符合拍摄车辆损伤特征的预定要求之前，所述方法还包括：
    将所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务 器判断所述第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果；
    接收所述定损服务器发送的所述判断结果；
    所述如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损，包括：
    如果所述判断结果指示所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
  6. 根据权利要求1-5中任一项所述的方法，所述第一视频图像符合拍摄标识的预定要求，包括：
    从所述第一视频图像中确定所述目标车辆的标识所在的第一区域；
    通过预设的捕捉单元填充所述第一区域，得到捕捉单元组成的第二区域；
    如果所述第二区域中的视频图像符合拍摄标识的预定要求，则将所述第二区域突出显示，以确定所述第一视频图像符合拍摄标识的预定要求。
  7. 根据权利要求1-5中任一项所述的方法，所述第二视频图像符合拍摄车辆损伤特征的预定要求，包括：
    从所述第二视频图像中确定所述目标车辆的损伤相关的第三区域；
    通过预设的捕捉单元填充所述第三区域，得到捕捉单元组成的第四区域；
    如果所述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将所述第四区域突出显示，以确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
  8. 根据权利要求1所述的方法，所述基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损，包括：
    将所述第一视频图像和所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器根据所述第一视频图像和所述第二视频图像对所述 目标车辆进行定损，得到所述目标车辆的定损结果；
    接收所述定损服务器发送的所述定损结果。
  9. 一种车辆定损的装置，所述装置包括：
    第一视频采集模块，用于采集包括待定损的目标车辆的标识的第一视频图像；
    第二视频采集模块，用于如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
    车辆定损模块，用于如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
  10. 根据权利要求9所述的装置，所述第二视频图像包括第三视频图像和第四视频图像，所述车辆定损模块，包括：
    第三视频采集单元，用于继续采集用于判定所述目标车辆的损伤部位的第三视频图像；
    第四视频采集单元，用于如果所述第三视频图像能够判定所述目标车辆的损伤部位，则继续采集用于判定所述目标车辆的损伤程度的第四视频图像；
    判定单元，用于如果所述第四视频图像能够判定所述目标车辆的损伤程度，则确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
  11. 根据权利要求10所述的装置，所述第二视频采集模块，包括：
    特征提取单元，用于从所述第一视频图像中提取与所述目标车辆的标识相关的图像特征；
    判断单元，用于如果提取的图像特征与设定的车辆标识的特征相匹配，则确定第一视频图像符合拍摄标识的预定要求。
  12. 根据权利要求11所述的装置，所述车辆标识的特征包括以下一个或多个的组合：车牌号码、前大灯、轮毂、车门把手、车辆尾灯、车辆后视镜、油箱盖和充电口。
  13. 根据权利要求12所述的装置，所述装置还包括：
    视频图像发送模块，用于将所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器判断所述第二视频图像是否符合拍摄车辆损伤特征的预定要求，得到判断结果；
    判断结果接收模块，用于接收所述定损服务器发送的所述判断结果；
    所述车辆定损模块，用于如果所述判断结果指示所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
  14. 根据权利要求9-13中任一项所述的装置，所述第二视频采集模块，包括：
    第一区域确定单元，用于从所述第一视频图像中确定所述目标车辆的标识所在的第一区域；
    第一填充单元，用于通过预设的捕捉单元填充所述第一区域，得到捕捉单元组成的第二区域；
    第一判定单元，用于如果所述第二区域中的视频图像符合拍摄标识的预定要求，则将所述第二区域突出显示，以确定所述第一视频图像符合拍摄标识的预定要求。
  15. 根据权利要求9-13中任一项所述的装置，所述车辆定损模块，包括：
    第三区域确定单元，用于从所述第二视频图像中确定所述目标车辆的损伤相关的第三区域；
    第二填充单元，用于通过预设的捕捉单元填充所述第三区域，得到捕捉单元组成的第四区域；
    第二判定单元，用于如果所述第四区域中的视频图像符合拍摄车辆损伤特征的预定要求，则将所述第四区域突出显示，以确定所述第二视频图像符合拍摄车辆损伤特征的预定要求。
  16. 根据权利要求9所述的装置，所述车辆定损模块，包括：
    视频图像发送单元，用于将所述第一视频图像和所述第二视频图像发送给车辆定损服务器，以使所述车辆定损服务器根据所述第一视频图像和所述第二视频图像对所述目标车辆进行定损，得到所述目标车辆的定损结果；
    定损结果接收单元，用于接收所述定损服务器发送的所述定损结果。
  17. 一种车辆定损的设备，所述车辆定损的设备包括：
    处理器；以及
    被安排成存储计算机可执行指令的存储器，所述可执行指令在被执行时使所述处理器：
    采集包括待定损的目标车辆的标识的第一视频图像；
    如果所述第一视频图像符合拍摄标识的预定要求，则继续采集包括所述目标车辆的损伤相关的第二视频图像；
    如果所述第二视频图像符合拍摄车辆损伤特征的预定要求，则基于所述第一视频图像和所述第二视频图像，对所述目标车辆进行定损。
PCT/CN2018/123336 2018-03-27 2018-12-25 一种车辆定损的方法、装置及设备 WO2019184479A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US16/918,888 US11087138B2 (en) 2018-03-27 2020-07-01 Vehicle damage assessment method, apparatus, and device
US17/370,984 US20210334548A1 (en) 2018-03-27 2021-07-08 Vehicle damage assessment method, apparatus, and device

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201810259950.4 2018-03-27
CN201810259950.4A CN108647563A (zh) 2018-03-27 2018-03-27 一种车辆定损的方法、装置及设备

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US16/918,888 Continuation US11087138B2 (en) 2018-03-27 2020-07-01 Vehicle damage assessment method, apparatus, and device

Publications (1)

Publication Number Publication Date
WO2019184479A1 true WO2019184479A1 (zh) 2019-10-03

Family

ID=63744841

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/123336 WO2019184479A1 (zh) 2018-03-27 2018-12-25 一种车辆定损的方法、装置及设备

Country Status (4)

Country Link
US (2) US11087138B2 (zh)
CN (1) CN108647563A (zh)
TW (1) TWI740088B (zh)
WO (1) WO2019184479A1 (zh)

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108647563A (zh) * 2018-03-27 2018-10-12 阿里巴巴集团控股有限公司 一种车辆定损的方法、装置及设备
CN109635651B (zh) * 2018-11-07 2024-05-24 中国平安财产保险股份有限公司 一种基于图像识别的车辆定损方法、存储介质及服务器
JP7263983B2 (ja) * 2019-08-30 2023-04-25 富士通株式会社 撮影漏れ検出装置、及び、撮影漏れ検出方法
US10814800B1 (en) * 2019-12-06 2020-10-27 Degould Limited Vehicle imaging station
CN111612104B (zh) * 2020-06-30 2021-04-13 爱保科技有限公司 车辆定损图像获取方法、装置、介质和电子设备
US11769120B2 (en) * 2020-10-14 2023-09-26 Mitchell International, Inc. Systems and methods for improving user experience during damage appraisal
CN112632329A (zh) * 2020-12-18 2021-04-09 咪咕互动娱乐有限公司 视频提取方法、装置、电子设备及存储介质
KR102367231B1 (ko) * 2021-01-04 2022-02-25 쿠팡 주식회사 작업자가 작업을 수행하도록 하는 방법 및 장치
US11919479B2 (en) * 2021-05-18 2024-03-05 Ford Global Technologies, Llc Systems and methods for providing security to a vehicle
CN113486725A (zh) * 2021-06-11 2021-10-08 爱保科技有限公司 智能车辆定损方法及装置、存储介质及电子设备

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106127142A (zh) * 2016-06-21 2016-11-16 北京小米移动软件有限公司 对象追踪方法及装置
CN106658173A (zh) * 2017-02-16 2017-05-10 成都市极米科技有限公司 一种视频显示方法、装置及系统
CN107368776A (zh) * 2017-04-28 2017-11-21 阿里巴巴集团控股有限公司 车辆定损图像获取方法、装置、服务器和终端设备
CN108647563A (zh) * 2018-03-27 2018-10-12 阿里巴巴集团控股有限公司 一种车辆定损的方法、装置及设备

Family Cites Families (31)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6696978B2 (en) * 2001-06-12 2004-02-24 Koninklijke Philips Electronics N.V. Combined laser/radar-video speed violation detector for law enforcement
US20040032906A1 (en) * 2002-08-19 2004-02-19 Lillig Thomas M. Foreground segmentation for digital video
US7809587B2 (en) * 2004-05-07 2010-10-05 International Business Machines Corporation Rapid business support of insured property using image analysis
US20060269105A1 (en) * 2005-05-24 2006-11-30 Langlinais Ashton L Methods, Apparatus and Products for Image Capture
KR20090063406A (ko) * 2007-12-14 2009-06-18 삼성전자주식회사 전송 특성을 고려한 실시간 동영상 화질 평가 시스템 및방법
US8483440B2 (en) * 2011-04-13 2013-07-09 Xerox Corporation Methods and systems for verifying automatic license plate recognition results
US9760789B2 (en) * 2012-04-17 2017-09-12 Conduent Business Services, Llc Robust cropping of license plate images
US8774465B2 (en) * 2012-06-12 2014-07-08 State Farm Mutual Automobile Insurance Company System and method for providing automotive purchase, insurance quote, and vehicle financing information using vehicle recognition
US10783585B1 (en) * 2012-08-16 2020-09-22 Allstate Insurance Company Agent-facilitated claims damage estimation
US9407874B2 (en) * 2013-04-30 2016-08-02 Esurance Insurance Services, Inc. Remote claims adjuster
US9070289B2 (en) * 2013-05-10 2015-06-30 Palo Alto Research Incorporated System and method for detecting, tracking and estimating the speed of vehicles from a mobile platform
US9025825B2 (en) * 2013-05-10 2015-05-05 Palo Alto Research Center Incorporated System and method for visual motion based object segmentation and tracking
FR3007172B1 (fr) * 2013-06-12 2020-12-18 Renault Sas Procede et systeme d'identification d'un degat cause a un vehicule
US10410278B2 (en) * 2013-07-25 2019-09-10 The Crawford Group, Inc. Method and apparatus for integrated image capture for vehicles to track damage
TWM478859U (zh) * 2014-01-09 2014-05-21 Han-Wei Chang 人車路交通事故影音自動分析系統
US10867327B1 (en) * 2014-06-27 2020-12-15 Blinker, Inc. System and method for electronic processing of vehicle transactions based on image detection of vehicle license plate
US10089396B2 (en) * 2014-07-30 2018-10-02 NthGen Software Inc. System and method of a dynamic interface for capturing vehicle data
JP6387782B2 (ja) * 2014-10-17 2018-09-12 ソニー株式会社 制御装置、制御方法及びコンピュータプログラム
CN105894817B (zh) * 2015-01-26 2019-04-30 杭州海康威视数字技术股份有限公司 车辆违章停车的取证方法及其装置
US9619701B2 (en) * 2015-05-20 2017-04-11 Xerox Corporation Using motion tracking and image categorization for document indexing and validation
CN104932359B (zh) * 2015-05-29 2019-01-08 大连楼兰科技股份有限公司 基于cae技术的车辆远程无人定损系统及定损方法
US9824453B1 (en) * 2015-10-14 2017-11-21 Allstate Insurance Company Three dimensional image scan for vehicle
US20170147990A1 (en) * 2015-11-23 2017-05-25 CSI Holdings I LLC Vehicle transactions using objective vehicle data
US10692050B2 (en) * 2016-04-06 2020-06-23 American International Group, Inc. Automatic assessment of damage and repair costs in vehicles
US9886771B1 (en) * 2016-05-20 2018-02-06 Ccc Information Services Inc. Heat map of vehicle damage
GB2554361B8 (en) * 2016-09-21 2022-07-06 Emergent Network Intelligence Ltd Automatic image based object damage assessment
US10255521B2 (en) * 2016-12-12 2019-04-09 Jack Cooper Logistics, LLC System, method, and apparatus for detection of damages on surfaces
US10657707B1 (en) * 2017-01-09 2020-05-19 State Farm Mutual Automobile Insurance Company Photo deformation techniques for vehicle repair analysis
JP6768557B2 (ja) * 2017-02-27 2020-10-14 パナソニックｉ−ＰＲＯセンシングソリューションズ株式会社 監視カメラシステム及び監視方法
CN107194323B (zh) * 2017-04-28 2020-07-03 阿里巴巴集团控股有限公司 车辆定损图像获取方法、装置、服务器和终端设备
CN107563893A (zh) * 2017-08-31 2018-01-09 济南浪潮高新科技投资发展有限公司 一种车险理赔方法、客户端、服务器以及系统

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106127142A (zh) * 2016-06-21 2016-11-16 北京小米移动软件有限公司 对象追踪方法及装置
CN106658173A (zh) * 2017-02-16 2017-05-10 成都市极米科技有限公司 一种视频显示方法、装置及系统
CN107368776A (zh) * 2017-04-28 2017-11-21 阿里巴巴集团控股有限公司 车辆定损图像获取方法、装置、服务器和终端设备
CN108647563A (zh) * 2018-03-27 2018-10-12 阿里巴巴集团控股有限公司 一种车辆定损的方法、装置及设备

Also Published As

Publication number Publication date
TWI740088B (zh) 2021-09-21
US20210334548A1 (en) 2021-10-28
CN108647563A (zh) 2018-10-12
TW201942793A (zh) 2019-11-01
US11087138B2 (en) 2021-08-10
US20200334467A1 (en) 2020-10-22

Similar Documents

Publication Publication Date Title
WO2019184479A1 (zh) 一种车辆定损的方法、装置及设备
TWI726194B (zh) 基於圖像的車輛定損方法、裝置及電子設備
KR102373251B1 (ko) 차량 보험 이미지 처리 방법, 장치, 서버 및 시스템
CN108280524B (zh) 识别车辆和生成预约信息的系统和方法
US11393256B2 (en) Method and device for liveness detection, and storage medium
TW201837786A (zh) 基於圖像的車輛定損方法、裝置、電子設備及系統
CN104239386B (zh) 用于对面部识别匹配区分优先级的方法和系统
CN112329881B (zh) 车牌识别模型训练方法、车牌识别方法及装置
CN107665588B (zh) 检测器状态异常的泊位的检测方法和系统
US20230177954A1 (en) Systems and methods for identifying vehicles using wireless device identifiers
CN115294538A (zh) 障碍物检测方法及装置、存储介质、终端
CN115861916A (zh) 异常停车行为检测方法、装置、计算机设备和存储介质
Jin et al. A deep-learning-based scheme for detecting driver cell-phone use
CN110880205B (zh) 一种停车收费方法及装置
TW202121326A (zh) 用車支付方法、裝置、系統及電子設備
CN111709377A (zh) 特征提取方法、目标重识别方法、装置及电子设备
CN103106400B (zh) 一种人脸检测方法与装置
CN111931721B (zh) 年检标签颜色和个数的检测方法、装置及电子设备
CN116012831A (zh) 基于区块链的智慧城市海量汽车停放智能结算方法和系统
CN116415961A (zh) 一种信息验证的方法、装置、存储介质及电子设备
CN111063063B (zh) 共享车辆解锁方法、装置、计算机设备和存储介质
CN114078235A (zh) 基于图像识别的轨道交通费用结算方法和装置
CN115131726A (zh) 一种车位检测方法、装置、设备及介质
JP6175904B2 (ja) 照合対象抽出システム、照合対象抽出方法、照合対象抽出プログラム
TW201729142A (zh) 即時車牌辨識系統及其方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18911594

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18911594

Country of ref document: EP

Kind code of ref document: A1