CN115065963A - Vehicle vision tracking and non-inductive alarm method based on face recognition - Google Patents
Vehicle vision tracking and non-inductive alarm method based on face recognition Download PDFInfo
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- CN115065963A CN115065963A CN202210529607.3A CN202210529607A CN115065963A CN 115065963 A CN115065963 A CN 115065963A CN 202210529607 A CN202210529607 A CN 202210529607A CN 115065963 A CN115065963 A CN 115065963A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/90—Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/06—Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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Abstract
The invention discloses a vehicle vision tracking and non-sensory alarm method based on facial recognition, which belongs to the technical field of facial recognition and solves the problem that in the prior art, a vehicle cannot automatically acquire information of surrounding environment to be compared with information in a database so as to recognize characteristics, so that various sudden events cannot be determined due to no related functions in the environment of tracking criminals and the like. The vehicle intelligent computing platform can allocate vehicle intelligent equipment, which comprises a camera, a radar, a mobile monitoring system and an environment recognition and recording system; the vehicle-mounted network communication system can upload information to the background server and broadcast the information in a limited area, and vehicles or equipment with the same capacity can enter an alert and monitoring state at the same time; a background server: the signal can be detected and reported to the public security system or to the information spread in the reverse limited area.
Description
Technical Field
The invention relates to the technical field of facial recognition, in particular to a vehicle visual tracking and non-sensory alarm method based on facial recognition.
Background
Different types of public safety events can be encountered in life, the tracking, the stealing and the robbery, the traffic accident escape, the driving of a front vehicle or the violation of parking and the like are included according to different types, and meanwhile, the events have sudden characteristics and are difficult to capture key information in time.
At present, the intelligent vehicle has the external radar monitoring and camera shooting capabilities, the vehicle can realize automatic driving, can acquire the obstacle information of the surrounding environment to judge the driving, can assist a public security task, plays social benefits and simultaneously improves brand reputation.
In the prior art, patent document CN108189804B discloses a "face recognition system and a face recognition method for a vehicle", which can perform local in-vehicle user information recognition and corresponding function linkage by operating a local and cloud information base. Patent document CN110766970B discloses a "server, a mobile terminal, a face recognizer, and a vehicle-finding control method", which provides a navigation route to a user based on mobile-side face recognition linked vehicle position information.
However, in the prior art, it is not proposed that a vehicle can automatically collect information of the surrounding environment and compare the information with information in a database so as to identify characteristics, so that under the environment of tracking criminals and the like, various sudden events cannot be determined due to no related functions.
Disclosure of Invention
The invention solves the problem that in the prior art, because the vehicle can not automatically acquire the information of the surrounding environment and compare the information with the information in the database so as to identify the characteristics, under the environment of tracking criminals and the like, a plurality of emergent events can not be determined because of no related functions.
The invention relates to a vehicle visual tracking and non-sensory alarm method based on facial recognition, which comprises the following steps of:
step S1, the background server issues the broadcast information to the vehicle at fixed point, and the background server and the equipment broadcast the police standby requirement information through the V2X environment;
step S2, the vehicle receives the broadcast information through the vehicle network communication system, and the vehicle intelligent computing platform makes a decision, if the enabling condition is met, whether the vehicle enters the tracking mode is prompted through the interactive interface, and if the enabling condition is met, the vehicle enters the tracking mode; or an enabled automatic tracking mode is set on the interactive interface before, and meanwhile, the received broadcast information is recorded into a vehicle-mounted alarm information base locally stored in the vehicle, so that the vehicle enters the tracking mode;
step S3, the vehicle enters a tracking mode, and the vehicle intelligent computing platform automatically calls the environment acquisition system capability;
step S4, the vehicle intelligent computing platform checks the collected information of the vehicle with the collected data of the vehicle alarm information base which is recorded before, confirms the identity of the target object, automatically allocates the tracking ability and continuously tracks the moving track of the target object;
step S5, the vehicle intelligent computing platform calls the vehicle-mounted automatic information recognition and recording system to start to automatically record key information and attach environmental information;
step S6, the vehicle intelligent computing platform sends the key information to the background through the vehicle network communication system, and broadcasts the key information to the surrounding vehicles or the intelligent devices with the same ability;
when the target object has left the vehicle monitoring area or environment, the vehicle exits the tracking mode and is notified via the interactive interface, step S7.
Further, in an embodiment of the present invention, the interactive interface is a center control screen or a mobile phone APP.
Further, in an embodiment of the present invention, in step S3, the environment acquisition system is a radar system, a mobile monitoring system, or a vehicle-mounted camera;
the mobile monitoring system is an unmanned aerial vehicle or an unmanned vehicle.
Further, in an embodiment of the present invention, in the step S3, the environment collecting system capability includes identification of surrounding people information features and identification of surrounding mobile vehicles.
Further, in an embodiment of the present invention, the identifying of the information features of the surrounding people includes clothing features, motion directions, displacement tracks and face features;
the identification of the surrounding mobile vehicles comprises vehicle appearance characteristics;
the vehicle appearance characteristics comprise brands, license plate numbers, running speeds and running directions.
Further, in an embodiment of the present invention, in step S5, the output format of the recording key information includes audio and video, pictures and translated words.
Further, in an embodiment of the present invention, in the step S5, the environment information includes geographic information, weather information, and time information.
Further, in an embodiment of the present invention, in the step S1, the background server is configured to report the information dissemination in the system or the reverse limited area after detecting the signal.
Further, in an embodiment of the present invention, the vehicle intelligent computing platform is used for deploying vehicle intelligent equipment, an environment recognition and recording system.
Further, in an embodiment of the present invention, the vehicle-mounted network communication system is used for uploading information to a background server and broadcasting the information in a limited area, and vehicles or devices with the same capabilities enter a police-prepared state and a monitoring state at the same time.
The invention solves the problem that in the prior art, because the vehicle can not automatically acquire the information of the surrounding environment and compare the information with the information in the database so as to identify the characteristics, under the environment of tracking criminals and the like, a plurality of sudden events can not be determined because of no related functions. The method has the following specific beneficial effects:
1. according to the vehicle visual tracking and non-sensory alarm method based on facial recognition, the vehicle has the capability of intelligently judging and allocating vehicle equipment to perform automatic tracking, for example, the vehicle is recorded and transferred from a tail camera to a front camera, the unmanned aerial vehicle is automatically released to assist monitoring, and the like, and the vehicle can automatically acquire information of the surrounding environment and compare the information with information in a database so as to recognize the characteristics.
2. According to the vehicle vision tracking and non-sensory alarm method based on the face recognition, disclosed by the invention, the vehicle can recognize traffic information or pay through V2X in an unmanned state, so that the convenience is greatly increased.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a diagram of a vehicle visual tracking and non-sensory warning system physical architecture for facial recognition, according to an embodiment.
FIG. 2 is a vehicle visual tracking and non-sensory warning system information architecture diagram of facial recognition, according to an embodiment.
Detailed Description
Various embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings. The embodiments described by referring to the drawings are exemplary and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The vehicle visual tracking and non-sensory alarm method based on the facial recognition comprises the following steps:
step S1, the background server issues the broadcast information to the vehicle at fixed point, and the background server and the equipment broadcast the alarm requirement information through the V2X environment;
step S2, the vehicle receives the broadcast information through the vehicle network communication system, the vehicle intelligent computing platform makes a decision, if the enabling condition is satisfied, whether to enter the tracking mode is prompted through the interactive interface, and if the enabling condition is satisfied, the vehicle enters the tracking mode; or an enabled automatic tracking mode is set on the interactive interface before, and meanwhile, the received broadcast information is recorded into a vehicle-mounted alarm information base locally stored in the vehicle, so that the vehicle enters the tracking mode;
step S3, the vehicle enters a tracking mode, and the vehicle intelligent computing platform automatically calls the environment acquisition system capability;
step S4, the vehicle intelligent computing platform checks the collected information of the vehicle with the collected data of the vehicle alarm information base which is recorded before, confirms the identity of the target object, automatically allocates the tracking ability and continuously tracks the moving track of the target object;
step S5, the vehicle intelligent computing platform calls the vehicle-mounted automatic information recognition and recording system to start to automatically record key information and attach environmental information;
step S6, the vehicle intelligent computing platform sends the key information to the background through the vehicle network communication system, and broadcasts the key information to the surrounding vehicles or the intelligent devices with the same ability;
when the target object has left the vehicle monitoring area or environment, the vehicle exits the tracking mode and is notified via the interactive interface, step S7.
In this embodiment, the interactive interface is a central control screen or a mobile phone APP.
In this embodiment, in step S3, the environment acquisition system is a radar system, a mobile monitoring system, or a vehicle-mounted camera;
the mobile monitoring system is an unmanned aerial vehicle or an unmanned vehicle.
In this embodiment, in step S3, the environment acquisition system capability includes identification of surrounding people information features and identification of surrounding mobile vehicles.
In this embodiment, the identification of the information features of the surrounding people includes clothing features, a motion direction, a displacement track and face features;
the identification of the surrounding mobile vehicles comprises vehicle appearance characteristics;
the vehicle appearance characteristics comprise brands, license plate numbers, running speeds and running directions.
In this embodiment, in step S5, the output format of the recording key information includes audio and video, pictures, and translated words.
In this embodiment, in step S5, the environment information includes geographical information, weather information, and time information.
In this embodiment, in step S1, the backend server is configured to report the information to the system or the reverse limited area after detecting the signal.
In this embodiment, the vehicle intelligent computing platform is used for deploying vehicle intelligent equipment and an environment recognition and recording system.
In this embodiment, the vehicle-mounted network communication system is used for uploading information to the background server and broadcasting the information in a limited area, and vehicles or devices with the same capability enter police and monitoring states at the same time.
The embodiment is based on the vehicle vision tracking and non-sensory alarm method based on the facial recognition, and provides an actual embodiment by combining specific objects:
the vehicle intelligent computing platform can allocate vehicle intelligent equipment, and comprises a camera, a radar, a mobile monitoring system (comprising an unmanned aerial vehicle, an unmanned aerial vehicle and the like), an environment recognition and recording system;
the vehicle-mounted network communication system can upload information to the background server and broadcast the information in a limited area, and vehicles or equipment with the same capacity can enter an alert and monitoring state at the same time;
a background server: the signal can be detected and reported to the public security system or to the information spread in the reverse limited area.
As shown in fig. 1 and fig. 2, 1) the background directly distributes the broadcast information to the vehicles at fixed points and broadcasts the police-ready demand information with other intelligent vehicles or devices through the V2X environment;
2) the method comprises the steps that a vehicle receives broadcast information through a vehicle-mounted network communication system, and the vehicle is decided through a vehicle intelligent computing platform (the decision needs to consider the vehicle state, such as whether the power supply capacity is enough or not, whether network communication is stable or not, whether each monitoring device operates normally or not and the like), if all enabling conditions are met, an interaction interface (such as a central control screen or a mobile phone APP) prompts a vehicle owner or a user whether to enter a tracking mode or not, and if the vehicle owner or the user agrees, the vehicle enters the tracking mode; or the user sets an enabled automatic tracking mode in the system (through a central control screen or a mobile phone APP) before, and simultaneously inputs the received broadcast information into a vehicle-mounted alarm information base stored locally in the vehicle;
3) when a vehicle enters a tracking mode, the vehicle intelligent computing platform automatically calls the environment acquisition system capacity (such as a radar system, a mobile monitoring system, a vehicle-mounted camera and the like) including identification of information characteristics of surrounding people (including clothing characteristics, motion directions and displacement track joint characteristics), and identification of vehicle appearance characteristics (brand, license plate number, running speed and running direction) of surrounding mobile vehicles;
4) the vehicle intelligent computing platform checks the acquired information of the vehicle with the acquired data of a vehicle-mounted alarm information base input before, confirms the identity of the suspected object, automatically allocates the tracking capability and continuously tracks the moving track of the suspected object;
5) the vehicle intelligent computing platform calls a vehicle-mounted automatic information identification and recording system to start to automatically record key information (the recording output format comprises audio and video, pictures, translated words and the like) and attach environment information comprising geographic information, weather information, time information and the like;
6) the vehicle intelligent computing platform sends the key information to a background through a vehicle-mounted network communication system, and simultaneously broadcasts the key information to surrounding vehicles or intelligent equipment with the same capability;
7) when the target object leaves the vehicle monitoring area or environment, the vehicle exits the tracking mode and informs the vehicle owner or user through the central control screen or the mobile phone APP.
The active transverse stabilizing device and method with continuously adjustable rigidity proposed by the present invention are described in detail above, and the principle and the implementation manner of the present invention are explained in the present document by applying specific examples, and the description of the above examples is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A vehicle visual tracking and non-sensory alarm method based on facial recognition is characterized by comprising the following steps:
step S1, the background server issues the broadcast information to the vehicle at fixed point, and the background server and the equipment broadcast the police standby requirement information through the V2X environment;
step S2, the vehicle receives the broadcast information through the vehicle network communication system, and the vehicle intelligent computing platform makes a decision, if the enabling condition is met, whether the vehicle enters the tracking mode is prompted through the interactive interface, and if the enabling condition is met, the vehicle enters the tracking mode; or an enabled automatic tracking mode is set on the interactive interface before, and meanwhile, the received broadcast information is recorded into a vehicle-mounted alarm information base locally stored in the vehicle, so that the vehicle enters the tracking mode;
step S3, the vehicle enters a tracking mode, and the vehicle intelligent computing platform automatically calls the environment acquisition system capability;
step S4, the vehicle intelligent computing platform checks the collected information of the vehicle with the collected data of the vehicle alarm information base which is recorded before, confirms the identity of the target object, automatically allocates the tracking ability and continuously tracks the moving track of the target object;
step S5, the vehicle intelligent computing platform calls the vehicle-mounted automatic information recognition and recording system to start to automatically record key information and attach environmental information;
step S6, the vehicle intelligent computing platform sends the key information to the background through the vehicle network communication system, and broadcasts the key information to the surrounding vehicles or the intelligent devices with the same ability;
when the target object has left the vehicle monitoring area or environment, the vehicle exits the tracking mode and is notified via the interactive interface, step S7.
2. The vehicle visual tracking and non-sensory alarm method based on facial recognition according to claim 1, characterized in that the interactive interface is a center control screen or a mobile phone APP.
3. The method for visually tracking and non-sensory alarming of a vehicle based on facial recognition as claimed in claim 1, wherein in the step S3, the environment acquisition system is a radar system, a mobile surveillance system or a vehicle-mounted camera;
the mobile monitoring system is an unmanned aerial vehicle or an unmanned vehicle.
4. The method as claimed in claim 1, wherein in step S3, the environment capturing system capability includes identification of surrounding people information features and identification of surrounding mobile vehicles.
5. The vehicle vision tracking and non-sensory alarm method based on facial recognition is characterized in that the identification of the information characteristics of surrounding people comprises clothing characteristics, motion directions, displacement tracks and facial characteristics;
the identification of the surrounding mobile vehicles comprises vehicle appearance characteristics;
the vehicle appearance characteristics comprise brands, license plate numbers, running speeds and running directions.
6. The method as claimed in claim 1, wherein in step S5, the output format of the recorded key information includes audio/video, pictures and translated words.
7. The method for visually tracking and alerting based on facial recognition of a vehicle according to claim 1, wherein the environmental information comprises geographic information, weather information and time information in step S5.
8. The method as claimed in claim 1, wherein in step S1, the background server is used to report the information dissemination to the system or reverse limited area after detecting the signal.
9. The method of claim 1, wherein the vehicle intelligent computing platform is configured to deploy vehicle intelligent devices, environmental recognition and recording systems.
10. The vehicle vision tracking and non-sensory alarm method based on facial recognition as claimed in claim 1, characterized in that the vehicle network communication system is used for uploading information to a background server and broadcasting in a limited area, and vehicles or equipment with the same capability enter the alarm and monitoring state simultaneously.
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| CN202210529607.3A CN115065963A (en) | 2022-05-16 | 2022-05-16 | Vehicle vision tracking and non-inductive alarm method based on face recognition |
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| CN202210529607.3A CN115065963A (en) | 2022-05-16 | 2022-05-16 | Vehicle vision tracking and non-inductive alarm method based on face recognition |
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Citations (3)
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| CN113111749A (en) * | 2021-03-31 | 2021-07-13 | 王健 | Tracking system based on video monitoring AI analysis of urban mobile vehicle |
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- 2022-05-16 CN CN202210529607.3A patent/CN115065963A/en active Pending
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| CN105243851A (en) * | 2015-09-24 | 2016-01-13 | 上海车音网络科技有限公司 | Vehicle monitoring method and system |
| CN110276969A (en) * | 2018-03-13 | 2019-09-24 | 上海博泰悦臻电子设备制造有限公司 | A kind of auxiliary car tracing method and system based on car-mounted terminal, car-mounted terminal |
| CN113111749A (en) * | 2021-03-31 | 2021-07-13 | 王健 | Tracking system based on video monitoring AI analysis of urban mobile vehicle |
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