CN108932503A - The recognition methods of Chinese herbaceous peony obstacle and device, storage medium, terminal under bad weather - Google Patents
The recognition methods of Chinese herbaceous peony obstacle and device, storage medium, terminal under bad weather Download PDFInfo
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- CN108932503A CN108932503A CN201810802673.7A CN201810802673A CN108932503A CN 108932503 A CN108932503 A CN 108932503A CN 201810802673 A CN201810802673 A CN 201810802673A CN 108932503 A CN108932503 A CN 108932503A
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- obstacle
- information
- vehicle front
- herbaceous peony
- automobile
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
Abstract
The recognition methods and device, storage medium, terminal of Chinese herbaceous peony obstacle under a kind of bad weather, the described method includes: in response to detecting that automobile is in bad weather, the Chinese herbaceous peony information of the vehicle front is acquired, the Chinese herbaceous peony information includes the first image information of the vehicle front；Determine whether the Chinese herbaceous peony information further includes other elements according to the boisterous severe degree；The Chinese herbaceous peony information is analyzed, obstacle whether there is with the determination vehicle front.The scheme provided through the invention in inclement weather can precisely identify Chinese herbaceous peony obstacle, ensure the safety of user.
Description
Technical field
The present invention relates to intelligent automobile technical fields, more particularly to a kind of recognition methods of Chinese herbaceous peony obstacle under bad weather
And device, storage medium, terminal.
Background technique
Greatly developing and popularizing with automobile industry, more and more people get used to driving as daily trip
The vehicles also become one of emphasis concerned by people with the traffic safety during vehicle.
When especially driving a car in inclement weather, with greater need for the safety of effective guarantee car user.
But it is based on the prior art, can only actively be taken by driver in inclement weather reduces speed, opens fog lamp etc.
Measure carrys out guarantee driving safety, and can not provide a kind of more intelligent, automation operation safety scheme.
Summary of the invention
Present invention solves the technical problem that being how to improve the identification precision of Chinese herbaceous peony obstacle under bad weather.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of recognition methods of Chinese herbaceous peony obstacle under bad weather,
It include: to acquire the Chinese herbaceous peony information of the vehicle front, the Chinese herbaceous peony information includes in response to detecting that automobile is in bad weather
First image information of the vehicle front；Determine whether the Chinese herbaceous peony information also wraps according to the boisterous severe degree
Include other elements；The Chinese herbaceous peony information is analyzed, obstacle whether there is with the determination vehicle front.
Optionally, the automobile refers in bad weather: the low visibility of the automobile local environment is default in first
Threshold value.
Optionally, the visibility of the automobile local environment is according to the automobile collected in history preset time period
What second image information in front determined.
Optionally, the first image information and second image information collecting are from different picture pick-up devices.
Optionally, the analysis Chinese herbaceous peony information, whether there is obstacle with the determination vehicle front includes: to described
First image information carries out image recognition processing；Processing result and default template are matched, the default template is selected from default
Template library is simultaneously associated with the boisterous type and/or severe degree；The vehicle front is determined according to matching result
With the presence or absence of obstacle.
Optionally, described includes: identification the first image letter to the first image information progress image recognition processing
Object in breath；The attribute information of the object recognized is analyzed, to obtain the processing result, the attribute information is selected from object
Weight, volume, shape.
Optionally, the default template is stored with the attribute information of at least one object determined according to historical data and is
The no judging result for obstacle；It is described that processing result and default template match includes: the object recognized according to
Attribute information searches the default template；Determine whether the object is obstacle according to lookup result, to obtain the matching knot
Fruit.
Optionally, the other elements of the Chinese herbaceous peony information are the sensor monitoring data of the vehicle front.
Optionally, described to determine whether the Chinese herbaceous peony information further includes other yuan according to the boisterous severe degree
Element includes: to determine that the Chinese herbaceous peony information only includes described when the boisterous severe degree is lower than the second preset threshold
First image information；When the boisterous severe degree is higher than second preset threshold, the Chinese herbaceous peony information is determined
It further include the sensor monitoring data.
Optionally, the sensor monitoring data are acquired from infrared sensor, ultrasonic sensor.
Optionally, the analysis Chinese herbaceous peony information, whether there is obstacle with the determination vehicle front includes: to described
First image information carries out image recognition processing；Processing result and default template are matched, the default template is selected from default
Template library is simultaneously associated with the boisterous type and/or severe degree；In conjunction with matching result and the vehicle front
Sensor monitoring data determine the vehicle front with the presence or absence of obstacle.
Optionally, before the sensor monitoring data of the combination matching result and the vehicle front determine the automobile
Side includes: when the sensor monitoring data of the vehicle front show there are when obstacle, alternatively, when described with the presence or absence of obstacle
Sensor monitoring data with result and vehicle front show that there are when obstacle, determine that there are obstacles for the vehicle front.
Optionally, the recognition methods further include: there are obstacles in response to the determination vehicle front, issue early warning letter
Breath.
Optionally, the recognition methods further include: there are obstacles in response to the determination vehicle front, identify the automobile
The distance between described obstacle；When the distance between the automobile and the obstacle are less than default safe distance, report is issued
Alert information.
In order to solve the above technical problems, the embodiment of the present invention also provides a kind of identification dress of Chinese herbaceous peony obstacle under bad weather
It sets, comprising: acquisition module acquires the Chinese herbaceous peony information of the vehicle front in response to detecting that automobile is in bad weather, described
Chinese herbaceous peony information includes the first image information of the vehicle front；Determining module, it is true according to the boisterous severe degree
Whether the fixed Chinese herbaceous peony information further includes other elements；Analysis module, for analyzing the Chinese herbaceous peony information, with the determination automobile
Front whether there is obstacle.
Optionally, the automobile refers in bad weather: the low visibility of the automobile local environment is default in first
Threshold value.
Optionally, the visibility of the automobile local environment is according to the automobile collected in history preset time period
What second image information in front determined.
Optionally, the first image information and second image information collecting are from different picture pick-up devices.
Optionally, the analysis module includes: the first identifying processing submodule, for carrying out to the first image information
Image recognition processing；First matched sub-block, for processing result and default template to match, the default template is selected from pre-
If template library is simultaneously associated with the boisterous type and/or severe degree；First determines submodule, for according to matching
As a result determine the vehicle front with the presence or absence of obstacle.
Optionally, the first identifying processing submodule includes: recognition unit, for identification in the first image information
Object；Analytical unit, for analyzing the attribute information of the object recognized, to obtain the processing result, the attribute letter
Breath is selected from weight, volume, the shape of object.
Optionally, the default template is stored with the attribute information of at least one object determined according to historical data and is
The no judging result for obstacle；First matched sub-block includes: searching unit, the object for recognizing according to
Attribute information searches the default template；First determination unit, for determining whether the object is obstacle according to lookup result,
To obtain the matching result.
Optionally, the other elements of the Chinese herbaceous peony information are the sensor monitoring data of the vehicle front.
Optionally, the determining module includes: second to determine submodule, when the boisterous severe degree is lower than the
When two preset thresholds, determine that the Chinese herbaceous peony information only includes the first image information；Alternatively, third determines submodule, work as institute
When stating boisterous severe degree higher than second preset threshold, determine that the Chinese herbaceous peony information further includes the sensor prison
Measured data.
Optionally, the sensor monitoring data are acquired from infrared sensor, ultrasonic sensor.
Optionally, the analysis module includes: the second identifying processing submodule, for carrying out to the first image information
Image recognition processing；Second matched sub-block, for processing result and default template to match, the default template is selected from pre-
If template library is simultaneously associated with the boisterous type and/or severe degree；4th determines submodule, for combining matching
As a result and the sensor monitoring data of the vehicle front determine the vehicle front with the presence or absence of obstacle.
Optionally, the described 4th determine that submodule includes: the second determination unit, when the sensor of the vehicle front monitors
Statistics indicate that there are when obstacle, alternatively, when the sensor monitoring data of the matching result and vehicle front show that there are obstacles
When, determine that there are obstacles for the vehicle front.
Optionally, the identification device further include: warning module, there are obstacle, hairs in response to the determination vehicle front
Warning information out.
Optionally, the identification device further include: apart from identification module, there is barrier in response to the determination vehicle front
Hinder, identifies the distance between the automobile and the obstacle；Alarm module, when the distance between the automobile and the obstacle are small
When default safe distance, alert.
In order to solve the above technical problems, the embodiment of the present invention also provides a kind of storage medium, it is stored thereon with computer and refers to
The step of enabling, the above method executed when the computer instruction is run.
In order to solve the above technical problems, the embodiment of the present invention also provides a kind of terminal, including memory and processor, it is described
The computer instruction that can be run on the processor is stored on memory, the processor runs the computer instruction
The step of Shi Zhihang above method.
Compared with prior art, the technical solution of the embodiment of the present invention has the advantages that
The embodiment of the present invention provides a kind of recognition methods of Chinese herbaceous peony obstacle under bad weather, comprising: in response to detecting vapour
Vehicle is in bad weather, acquires the Chinese herbaceous peony information of the vehicle front, and the Chinese herbaceous peony information includes the first of the vehicle front
Image information；Determine whether the Chinese herbaceous peony information further includes other elements according to the boisterous severe degree；Analysis institute
Chinese herbaceous peony information is stated, obstacle whether there is with the determination vehicle front.Conscious severe of driver is depended on compared with existing
Weather down train safety guarantee scheme, the scheme of the embodiment of the present invention are based on collected Chinese herbaceous peony accurate information and identify vehicle front
Whether there are obstacles.Specifically, the Chinese herbaceous peony information includes the first image information of the vehicle front.It is disliking as a result,
When user's naked eyes can not see Chinese herbaceous peony situation clearly under bad weather (such as heavy rain day, the big lower scene of snowy day visibility), the present invention
The scheme of embodiment is analyzed by the first image information to the vehicle front taken (such as to the first image information
Carry out image recognition processing), the discrimination and identification precision to Chinese herbaceous peony obstacle can be greatlyd improve, it is artificial to maximize reduction
Interference of the factor to recognition result, ensures the safety of user.Further, the scheme of the embodiment of the present invention is also according to severe day
The severe degree of gas determines the need for increasing other elements as auxiliary information, to further increase the identification to Chinese herbaceous peony obstacle
Precision.
Further, the analysis Chinese herbaceous peony information, whether there is obstacle with the determination vehicle front includes: to described
First image information carries out image recognition processing；Processing result and default template are matched, the default template is selected from default
Template library is simultaneously associated with the boisterous type and/or severe degree；The vehicle front is determined according to matching result
With the presence or absence of obstacle.The default template library can be for the bad weather storage pair of different type, different severe degree as a result,
The presetting module answered, when executing the scheme of the embodiment of the present invention, according to the concrete type of current adverse weather and severe degree from
Most suitable default template is chosen in default template library, to improve the analysis precision to the first image information, is optimized to Chinese herbaceous peony
The recognition effect of obstacle.
Detailed description of the invention
Fig. 1 be the embodiment of the present invention a kind of bad weather under Chinese herbaceous peony obstacle recognition methods flow chart；
Fig. 2 is the schematic diagram of the embodiment of the present invention one typical application scenarios；
Fig. 3 is the flow chart of a specific embodiment of step S102 in Fig. 1；
Fig. 4 is the flow chart of a specific embodiment of step S103 in Fig. 1；
Fig. 5 is the flow chart of the another embodiment of step S103 in Fig. 1；
Fig. 6 be the embodiment of the present invention a kind of bad weather under Chinese herbaceous peony obstacle identification device structural schematic diagram.
Specific embodiment
It will be appreciated by those skilled in the art that as described in the background art, in inclement weather, existing operation safety scheme
Consciously realizing for driver is depended on, and a kind of more intelligent, operation safety side for automating can not be provided
Case is seriously unfavorable for the safety of user.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of recognition methods of Chinese herbaceous peony obstacle under bad weather,
It include: to acquire the Chinese herbaceous peony information of the vehicle front, the Chinese herbaceous peony information includes in response to detecting that automobile is in bad weather
First image information of the vehicle front；Determine whether the Chinese herbaceous peony information also wraps according to the boisterous severe degree
Include other elements；The Chinese herbaceous peony information is analyzed, obstacle whether there is with the determination vehicle front.
It will be appreciated by those skilled in the art that the scheme of the embodiment of the present invention, which is based on collected Chinese herbaceous peony accurate information, identifies automobile
Whether there are obstacles in front.Specifically, the Chinese herbaceous peony information includes the first image information of the vehicle front.As a result,
When user's naked eyes can not see Chinese herbaceous peony situation clearly under bad weather (such as heavy rain day, the big lower scene of snowy day visibility), this
The scheme of inventive embodiments is analyzed by the first image information to the vehicle front taken (such as to the first image
Information carries out image recognition processing), the discrimination and identification precision to Chinese herbaceous peony obstacle can be greatlyd improve, maximizing reduces
Interference of the human factor to recognition result, ensures the safety of user.
Further, the scheme of the embodiment of the present invention determines the need for increasing other also according to boisterous severe degree
Element is as auxiliary information, to further increase the identification precision to Chinese herbaceous peony obstacle.
It is understandable to enable above-mentioned purpose of the invention, feature and beneficial effect to become apparent, with reference to the accompanying drawing to this
The specific embodiment of invention is described in detail.
Fig. 1 be the embodiment of the present invention a kind of bad weather under Chinese herbaceous peony obstacle recognition methods flow chart.Wherein, described
Bad weather may include that the lower possible influence car user of the visibility such as night, rainy day, snowy day, haze, greasy weather drives body
The weather conditions tested.
The scheme of the present embodiment can be adapted for the application scenarios such as family-sized car, freight, coach, all kinds of to ensure
Driver and passenger use the traffic safety during vehicle in inclement weather.
Specifically, the Chinese herbaceous peony obstacle may include the vehicle positioned at vehicle front, pedestrian, other object (such as stones, tree
Branch, animal) etc. may influence the automobile normally travel object.
Wherein, the vehicle front may include the front of the automobile, can also include the side front of the automobile,
Such as automobile front door to the region between headstock.
More specifically, with reference to Fig. 1, under bad weather described in the present embodiment the recognition methods of Chinese herbaceous peony obstacle may include as
Lower step:
Step S101 acquires the Chinese herbaceous peony information of the vehicle front in response to detecting that automobile is in bad weather, described
Chinese herbaceous peony information includes the first image information of the vehicle front.
Step S102 determines whether the Chinese herbaceous peony information further includes other yuan according to the boisterous severe degree
Element.
Step S103 analyzes the Chinese herbaceous peony information, whether there is obstacle with the determination vehicle front.
In one or more embodiments, the automobile is in bad weather and can refer to: the automobile local environment
Low visibility is in the first preset threshold.
Preferably, first preset threshold can be 3 meters.That is, when the low visibility of the automobile local environment is in 3
Meter Shi can determine the automobile current driving in bad weather.In practical applications, those skilled in the art can also basis
Need to adjust the specific value of first preset threshold, it will not be described here.
In one or more embodiments, the visibility of the automobile local environment can be according to history preset time period
What the second image information of the interior collected vehicle front determined.Wherein, the history preset time period can be for away from the present
10 minutes, away from modern half an hour or a longer period of time, those skilled in the art can according to need the adjustment history preset time
The specific value of section.
In one or more embodiments, the first image information can be acquired from second image information from different
Picture pick-up device.
Preferably, especially in bad weather conditions, for acquiring the camera shooting of the picture pick-up device of the first image information
Ability can be better than the shooting capacity for acquiring the picture pick-up device of second image information.The shooting capacity may include
Clarity, pixel size of captured image etc..
For example, the picture pick-up device for acquiring the first image information can be professional camera (such as night camera
Head), can have following performance: automatic light-supplementing；Shooting angle is adjustable；Shooting distance is adjustable.Specifically, the camera angle
It can be manually adjusted by user (the middle control screen as passed through automobile) with camera distance, alternatively, can also be by the picture pick-up device
From main regulation, or, it can also be controlled to adjust as the background server for executing scheme described in the present embodiment.
In another example the picture pick-up device for acquiring second image information can be common vehicle-mounted traveling recorder.
In a typical application scenarios, with reference to Fig. 2, automobile 21 can be equipped with automobile data recorder 22 and picture pick-up device
23, during automobile 21 travels, the automobile data recorder 22 is according to 21 front of the first preset interval (such as 1 second /) shooting automobile
The second image information and be uploaded to background server 24.Meanwhile the picture pick-up device 23 initially may be at dormant state.
Further, the background server 24 judges 21 local environment of automobile based on second image information
Whether visibility is lower than first preset threshold.
When judging result shows that the automobile 21 is in bad weather, the background server 24 wakes up the camera shooting and sets
Standby 23, and receive first image information in 21 front of the automobile that the picture pick-up device 23 takes.
As a change case, the background server 24 can be according to the second preset interval (such as 5 seconds /) actively from institute
It states automobile data recorder 22 and obtains collected newest first image information of automobile data recorder 22.Wherein, described second is pre-
If interval can be longer than the first preset interval, to reduce the data interaction frequency of the two, signaling consumption is reduced, energy consumption is reduced.
The background server 24 can be cloud server.
As another change case, the background server 24 can also be with the vehicle console of the automobile 21
(Automobile Console, abbreviation in control) 25 interaction, to obtain the real-time position information of the automobile 21, and then combines institute
The weather forecast for stating 21 their location of automobile determines whether the automobile 21 is in bad weather.
Further, the automobile 21 can by it is middle control 25 access car networkings, and be in together in the car networking
Background server 24 carries out data communication.
Further, the automobile data recorder 22 and 23 acquired image information of picture pick-up device can be by described
Control 25 is transmitted to the background server 24.The background server 24 can be the server for aiming at car networking system setting.
In one or more alternative embodiments, the automobile can also refer in bad weather: described in the automobile
The brightness of environment is lower than predetermined luminance threshold value.It is described to measure that other parameters can also be set as needed in those skilled in the art
Whether environment described in automobile is bad weather.
Further, the other elements of the Chinese herbaceous peony information can be the sensor monitoring data of the vehicle front.
For example, the sensor monitoring data can acquire self installation in infrared sensor, ultrasonic wave on the automobile
Sensor etc..
In one or more embodiments, it may include steps of with reference to Fig. 3, the step S102:
Step S1021, judges whether boisterous severe degree locating for the automobile is lower than the second preset threshold；
When the judging result of the step S1021 is affirmative, that is, when the boisterous severe degree is lower than the
When two preset thresholds, including step S1022, determine that the Chinese herbaceous peony information only includes the first image information；
Otherwise, when the judging result of the step S1021 is negative, that is, working as the boisterous severe degree
When higher than second preset threshold, including step S1023, determine that the Chinese herbaceous peony information further includes the sensor monitoring number
According to.
As a result, when the weather of the automobile local environment is excessively severe, if torrential rain, night are entirely without street lamp and environment
Light, big snowy day, serious haze etc. are conducive to more accurately analysis and identify the vapour by the auxiliary of the sensor monitoring data
Whether there are obstacles for front side, preferably to ensure the security of the lives and property of user.
Specifically, second preset threshold can be less than first preset threshold.
For example, described second is pre- when the low visibility that first preset threshold is the automobile local environment is in 3 meters
If threshold value can be the low visibility of the automobile local environment in 1 meter.
It in practical applications, can be to boisterous severe degree pre-classification, according to the tool of current adverse weather
The severe degree of body determines the element for needing the Chinese herbaceous peony information acquired to include.
Still shown in Fig. 2 for scene, the background server 24 is believed according to the second image that automobile data recorder 22 uploads
Current visibility is less than 3 meters around the determining automobile 21 of breath, and then wakes up the picture pick-up device 23 to obtain clarity more
The Front image (i.e. the first image information) of high, better quality the automobile 21.
Further, the first image information uploaded by analyzing the picture pick-up device 23, can determine the automobile 21
With the presence or absence of obstacle.
Further, during continuing in the automobile 21, if by (and/or the driving of the first image information
Recorder 22 continue upload the second image information) analysis shows visibility current around the automobile 21 further decreases
To less than 1 meter, at this point, for exempt from the first image information clarity is too low and the accuracy of impact analysis result, the backstage clothes
Business device 24 can wake up the sensor 26 being installed on the automobile 21, to control the sensor 26 to 21 front of automobile
Barrier carry out auxiliary monitoring.
Preferably, the sensor 26 can be installed on the headstock position of the automobile 21, more accurately to the vapour
The barrier in 21 front of vehicle is monitored.
Preferably, the sensor 26 can be infrared sensor and/or ultrasonic sensor.Those skilled in the art are also
It can according to need the other kinds of sensor of selection, it will not be described here.
In one or more embodiments, with reference to Fig. 4, when the judging result of the step S1021 is affirmative, that is,
When the boisterous severe degree is lower than the second preset threshold, the step S103 be may include steps of:
Step S1031 carries out image recognition processing to the first image information.
Step S1032 matches processing result and default template, the default template be selected from default template library and with institute
It states boisterous type and/or severe degree is associated.
Step S1033 determines the vehicle front with the presence or absence of obstacle according to matching result.
The default template library can store corresponding for the bad weather of different type, different severe degree as a result,
Presetting module, when executing the scheme of the embodiment of the present invention, according to the concrete type of current adverse weather and severe degree from default
Most suitable default template is chosen in template library, to improve the analysis precision to the first image information, is optimized to Chinese herbaceous peony obstacle
Recognition effect.
Specifically, multiple default templates that the default template library includes can be divided according to weather.For example, light rain, in
Rain and heavy rain can respectively correspond different default templates.
In one or more embodiments, the step S1031 may include step: in identification the first image information
Object；The attribute information of the object recognized is analyzed, to obtain the processing result, the attribute information is selected from the depth of object
Either shallow, volume, shape.
Still shown in Fig. 2 for scene, passes through the first image information uploaded to the picture pick-up device 22 and carry out image knowledge
Other places reason, the background server 24 therefrom extracts the tailstock portion image of automobile 27, and the automobile 27 is measured from figure
Tailstock portion dimension data.Meanwhile the background server 24 also extracts road ahead from the first image information
On there are stones 28.
In one or more embodiments, the default template can store at least one that with good grounds historical data determines
The attribute information of object and whether be obstacle judging result；The step S1032 may include step: be recognized according to described
The attribute information of object search the default template；Determine whether the object is obstacle according to lookup result, to obtain
State matching result.
For example, the historical data may include acquiring in history under different degrees of, different types of bad weather
To vehicle front image information analysis as a result, to establishing the default template library on the basis of big data analysis,
To determine suitably default template according to specific bad weather in subsequent applications, so according to the default template
Compare and determines whether the object currently recognized is barrier.
Preferably, various sizes of object of the same race can be understood as the object of different attribute information.For example, ratchel and small
Stone can be understood as the object with different attribute information, and the two is mutually independent to be stored in the default template and may be right
Answer different judging results.
Preferably for the object of same alike result information, corresponding judging result may be different in the default template of difference.
For example, the branch of the same size, may not be considered as obstacle in the default template of small rainy day, but presetting in the big rainy day
Obstacle may be identified as in template.
It whether is that the judging result of obstacle can be comprehensive statistics and go through preferably for the object of particular community information
The recognition result of the object of the attribute information is determined in history.
Still shown in Fig. 2 for scene, the dimension data and the stone in the tailstock portion of the automobile 27 are obtained in identification
After the dimension data of block 28, the background server 24 can be according to 21 current environment of automobile in default template library
Search suitably default template.
Further, the default template is searched according to the dimension data in the tailstock portion of the automobile 27, according to
The dimension data in the tailstock portion of automobile 27 determines whether the automobile 27 is obstacle.
In this scene, if being stored with corresponding record in the default template, and record shows that the automobile 27 is obstacle,
Then determine that automobile 27 described in current scene is obstacle.
Further, the default template is searched according to the dimension data of the stone 28, according to the stone 28
Dimension data determines whether the stone 28 is obstacle.
In this scene, if being stored with corresponding record in the default template, and it is barrier that record, which shows the stone 28 not,
Hinder, it is determined that stone 28 described in current scene is not obstacle.
Further, the default template library can store in the background server 24.Alternatively, the default template library
It is stored in other third-party server (such as cloud 29), the background server 24 with the cloud 29 by communicating
It interrogates to obtain the particular preset template of the default template library or the default template library.
In one or more alternative embodiments, if the dimension data in the tailstock portion of the automobile 27 and/or stone 28
Dimension data does not have matching result in the default template, then can compare dimension data and the vapour that this identification obtains
The dimension data of vehicle 21 itself, and determine whether the automobile 27 and/or stone 28 are obstacle according to comparison result.
For example, can the stone 28 dimension data and the automobile 21 chassis height, when the stone 28
Height be greater than the automobile 21 chassis height when, can determine the stone 28 be obstacle.
Further, the size number of the dimension data and/or stone 28 in the tailstock portion of this collected automobile 27
Accordingly and corresponding judging result can store into corresponding default template, for future use.
In one or more embodiments, with reference to Fig. 5, when the judging result of the step S1021 is negative, that is,
When the boisterous severe degree is higher than the second preset threshold, in Fig. 5 institute similar with above-mentioned embodiment illustrated in fig. 4
Stating step S103 also may include the step S1031 and step S1032, and be with the difference of above-mentioned embodiment illustrated in fig. 4,
In the present embodiment, step S1033 shown in above-mentioned Fig. 4 could alternatively be step S1033 ': in conjunction with matching result and described
The sensor monitoring data of vehicle front determine the vehicle front with the presence or absence of obstacle.
Wherein, above-mentioned embodiment illustrated in fig. 4 can be referred to about the particular content of the step S1031 and step S1032
In associated description, it will not be described here.
Further, the step S1033 ' may include step: when the sensor monitoring data table of the vehicle front
It is bright there are when obstacle, alternatively, when the sensor monitoring data of the matching result and vehicle front show to determine there are when obstacle
There are obstacles for the vehicle front.
It is described by matching the default template and determining that the automobile 27 is obstacle still shown in Fig. 2 for scene
After stone 28 is not obstacle, number can be monitored further combined with the sensor in 21 front of the automobile that the sensor 26 acquires
According to progress comprehensive analysis.
For the stone 28, if the sensor monitoring data in 21 front of the automobile that the sensor 26 acquires show
The stone 28 is not obstacle, and the undersize of stone 28 is as described in showing the sensor monitoring data to influence the automobile
21 normally travel can then determine that stone 28 described in current scene is not obstacle.
If the sensor monitoring data in 21 front of the automobile that the sensor 26 acquires show that the stone 28 is barrier
Hinder, although as described in being less placed exactly in 28 size of stone on the prediction driving trace of the tire of automobile 21, and it is described
First image information shows that the surface of the stone 28 is relatively sharp, then can determine that stone 28 described in current scene is obstacle.
For the automobile 27, if the sensor monitoring data in 21 front of the automobile that the sensor 26 acquires show
The automobile 27 is obstacle, then can determine that automobile 27 described in current scene is obstacle.
In one or more alternative embodiments, when the matching result shows there are obstacle, and the sensing of vehicle front
Device monitoring data show that there is no obstacles there is no that when obstacle, can determine the vehicle front.
Alternatively, to avoid judging by accident, when situation described in this alternative embodiment occurs, the vehicle-mounted loudspeaking of automobile can also be passed through
Device is prompted, to prompt occupant to pay attention to road ahead situation.
In one or more embodiments, recognition methods described in the present embodiment can also include: in response to the determination vapour
There are obstacles for front side, issue warning information.
Still for scene, determining that the background server 24 can there are after obstacle in front of the automobile 21 shown in Fig. 2
It is described pre- to be issued by the vehicle-mounted loudspeaker (not shown) of the middle 25 control automobile 21 of control, middle control screen (not shown) etc.
Alert information, to prompt occupant to pay attention to road ahead situation.
Preferably, the warning information can be issued in the form of prompt tone, voice broadcast, text etc..
In one or more embodiments, recognition methods described in the present embodiment can also include: in response to the determination vapour
There are obstacles for front side, identify the distance between the automobile and the obstacle；When between the automobile and the obstacle away from
When from being less than default safe distance, alert.
Still shown in Fig. 2 for scene, determining in front of the automobile 21 there are after obstacle (such as described automobile 27), it is described
Background server 24 can continue to analyze the Chinese herbaceous peony that the picture pick-up device 23 (or the picture pick-up device 23 and sensor 26) uploads
Information, to pay close attention to the distance between the automobile 27 and the automobile 21 L.
When the distance between the automobile 27 and the automobile 21 L are less than default safe distance (such as 6 meters), the backstage
Server 24 can control the associated components alert in the automobile 21.
Similar with the warning information, the warning message can also be sent out in the form of prompt tone, voice broadcast, text etc.
Out.
As a change case, determining in front of the automobile 21 there are after obstacle (such as described automobile 27), the backstage
Server can while the middle control screen for controlling automobile 21 shows warning information, identify the automobile 27 and the automobile 21 it
Between distance L control institute and when finding the automobile 27 distance L being less than default safe distance between the automobile 21
The vehicle-mounted loudspeaker alert of automobile 21 is stated, to ensure to cause the attention of occupant.
As another change case, determining in front of the automobile 21 there are after obstacle (such as described automobile 27), after described
Platform server can identify the automobile 27 and the automobile 21 while the middle control screen for controlling automobile 21 shows warning information
The distance between L can suspend transmission if the distance between the automobile 27 and the automobile 21 L are not further reduced
The warning information and/or warning message；It even contracts if the distance between the automobile 27 and the automobile 21 L is further reduced
When the small to less than described default safe distance, the vehicle-mounted loudspeaker that the background server 24 can control the automobile 21 is issued
Warning message, to ensure to cause the attention of occupant in time.
It is described while controlling the component sending warning message in the automobile 21 as another change case
Background server 24 can also be to the portable smart machines such as mobile phone, the IPAD of occupant or interested third party people
Member's (such as traffic police department, Security Personnel) issues the warning message.
Wherein, the application program for executing scheme described in the present embodiment can be installed on the smart machine
(Application, abbreviation APP), the application program can be interacted with the background server 24 to receive the backstage clothes
The warning information and/or warning message that business device 24 is sent.
The scheme for using the present embodiment as a result, whether there is based on collected Chinese herbaceous peony accurate information identification vehicle front
Barrier.Specifically, the Chinese herbaceous peony information may include the first image information of the vehicle front.As a result, in severe day
When user's naked eyes can not see Chinese herbaceous peony situation clearly under gas (such as heavy rain day, the big lower scene of snowy day visibility), the present invention is implemented
The scheme of example is analyzed by the first image information to the vehicle front taken and (is such as carried out to the first image information
Image recognition processing), the discrimination and identification precision to Chinese herbaceous peony obstacle can be greatlyd improve, maximizing reduces human factor
Interference to recognition result ensures the safety of user.
Further, the scheme of the embodiment of the present invention determines the need for increasing other also according to boisterous severe degree
Element is as auxiliary information, to further increase the identification precision to Chinese herbaceous peony obstacle.
Fig. 6 be the embodiment of the present invention a kind of bad weather under Chinese herbaceous peony obstacle identification device structural schematic diagram.Ability
Field technique personnel understand, the identification device 6 (hereinafter referred to as identification device 6) of Chinese herbaceous peony obstacle under bad weather described in the present embodiment
For implementing above-mentioned Fig. 1 to method and technology scheme described in embodiment illustrated in fig. 5.
Specifically, in the present embodiment, the identification device 6 may include: acquisition module 61, in response to detecting automobile
In bad weather, the Chinese herbaceous peony information of the vehicle front is acquired, the Chinese herbaceous peony information includes the first figure of the vehicle front
As information；Determining module 62 determines whether the Chinese herbaceous peony information further includes other yuan according to the boisterous severe degree
Element；Analysis module 63 whether there is obstacle for analyzing the Chinese herbaceous peony information with the determination vehicle front.
Further, the automobile is in bad weather and can refer to: the low visibility of the automobile local environment is in
One preset threshold.
Further, the visibility of the automobile local environment can be according to institute collected in history preset time period
State the second image information determination of vehicle front.
Further, the first image information can be acquired from second image information from different picture pick-up devices.
In one non-limiting embodiment, the analysis module 63 may include: the first identifying processing submodule 631,
For carrying out image recognition processing to the first image information；First matched sub-block 632 is used for processing result and presets
Template matches, and the default template is selected from default template library and related to the boisterous type and/or severe degree
Connection；First determines submodule 633, for determining the vehicle front with the presence or absence of obstacle according to matching result.
Further, the first identifying processing submodule 631 may include: recognition unit 6311, described for identification
Object in first image information；Analytical unit 6312, for analyzing the attribute information of the object recognized, to obtain the place
Reason is as a result, the attribute information is selected from weight, volume, the shape of object.
Further, the default template can store the attribute letter at least one object that with good grounds historical data determines
Breath and whether be obstacle judging result；First matched sub-block 632 may include: searching unit 6321, be used for basis
The attribute information of the object recognized searches the default template；First determination unit 6322, for according to lookup result
Determine whether the object is obstacle, to obtain the matching result.
Further, the other elements of the Chinese herbaceous peony information can be the sensor monitoring data of the vehicle front.
In one non-limiting embodiment, the determining module 62 may include: the second determining submodule 621, work as institute
When stating boisterous severe degree lower than the second preset threshold, determine that the Chinese herbaceous peony information only includes the first image letter
Breath；Alternatively, third determines submodule 622, when the boisterous severe degree is higher than second preset threshold, determine
The Chinese herbaceous peony information further includes the sensor monitoring data.
Further, the sensor monitoring data can be acquired from infrared sensor, ultrasonic sensor.
In one non-limiting embodiment, the analysis module 63 may include: the second identifying processing submodule 634,
For carrying out image recognition processing to the first image information；Second matched sub-block 635 is used for processing result and presets
Template matches, and the default template is selected from default template library and related to the boisterous type and/or severe degree
Connection；4th determination submodule 636, for described in the sensor monitoring data determination in conjunction with matching result and the vehicle front
Vehicle front whether there is obstacle.
Wherein, the second identifying processing submodule 634 can execute identical with the first identifying processing submodule 631
Function, the two can be the same module, or, or two mutually independent modules.
Similar, second matched sub-block 635 can execute identical function with first matched sub-block 632
Can, the two can be the same module, or, or two mutually independent modules.
Further, the described 4th determine that submodule 636 may include: the second determination unit 6361, before the automobile
The sensor monitoring data of side show there are when obstacle, alternatively, when the matching result and the sensor of vehicle front monitor number
According to showing that there are when obstacle, determine that there are obstacles for the vehicle front.
Further, the identification device 6 can also include: warning module 64, deposit in response to the determination vehicle front
In obstacle, warning information is issued.
Further, the identification device 6 can also include: apart from identification module 65, before the determination automobile
There are obstacles for side, identify the distance between the automobile and the obstacle；Alarm module 66, when the automobile and the obstacle it
Between distance be less than default safe distance when, alert.
Working principle, more contents of working method about the identification device 6, are referred to above-mentioned Fig. 1 into Fig. 5
Associated description, which is not described herein again.
Further, a kind of storage medium is also disclosed in the embodiment of the present invention, is stored thereon with computer instruction, the calculating
Above-mentioned Fig. 1 is executed to method and technology scheme described in embodiment illustrated in fig. 5 when machine instruction operation.Preferably, the storage is situated between
Matter may include non-volatile (non-volatile) memory or non-transient (non-transitory) memory etc.
Computer readable storage medium.The storage medium may include ROM, RAM, disk or CD etc..
Further, a kind of terminal, including memory and processor is also disclosed in the embodiment of the present invention, deposits on the memory
The computer instruction that can be run on the processor is contained, the processor executes above-mentioned when running the computer instruction
Fig. 1 is to method and technology scheme described in embodiment illustrated in fig. 5.Preferably, the terminal can be the background server,
It can be the intelligence for the application program (Application, abbreviation APP) that mobile phone etc. is equipped with for executing scheme described in the present embodiment
It can equipment.
Although present disclosure is as above, present invention is not limited to this.Anyone skilled in the art are not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (30)
1. the recognition methods of Chinese herbaceous peony obstacle under a kind of bad weather characterized by comprising
In response to detecting that automobile is in bad weather, the Chinese herbaceous peony information of the vehicle front is acquired, the Chinese herbaceous peony information includes
First image information of the vehicle front；
Determine whether the Chinese herbaceous peony information further includes other elements according to the boisterous severe degree；
The Chinese herbaceous peony information is analyzed, obstacle whether there is with the determination vehicle front.
2. recognition methods according to claim 1, which is characterized in that the automobile refers in bad weather: the vapour
The low visibility of vehicle local environment is in the first preset threshold.
3. recognition methods according to claim 2, which is characterized in that the visibility of the automobile local environment is that basis is gone through
The second image information of the collected vehicle front determines in history preset time period.
4. recognition methods according to claim 3, which is characterized in that the first image information and second image are believed
Breath is acquired from different picture pick-up devices.
5. recognition methods according to claim 1, which is characterized in that the analysis Chinese herbaceous peony information, described in determination
Vehicle front includes: with the presence or absence of obstacle
Image recognition processing is carried out to the first image information；
Processing result and default template are matched, the default template be selected from default template library and with the boisterous class
Type and/or severe degree are associated；
Determine the vehicle front with the presence or absence of obstacle according to matching result.
6. recognition methods according to claim 5, which is characterized in that described to carry out image knowledge to the first image information
It manages in other places
Identify the object in the first image information；
The attribute information of the object recognized is analyzed, to obtain the processing result, the attribute information is selected from the depth of object
Degree, volume, shape.
7. recognition methods according to claim 6, which is characterized in that the default template is stored with true according to historical data
The attribute information of at least one fixed object and whether be obstacle judging result；It is described by processing result and default template phase
With including:
The default template is searched according to the attribute information of the object recognized；
Determine whether the object is obstacle according to lookup result, to obtain the matching result.
8. recognition methods according to claim 1, which is characterized in that the other elements of the Chinese herbaceous peony information are the automobile
The sensor monitoring data in front.
9. recognition methods according to claim 8, which is characterized in that described true according to the boisterous severe degree
Whether the fixed Chinese herbaceous peony information further includes that other elements include:
When the boisterous severe degree is lower than the second preset threshold, determine that the Chinese herbaceous peony information only includes described first
Image information；
When the boisterous severe degree is higher than second preset threshold, determine that the Chinese herbaceous peony information further includes described
Sensor monitoring data.
10. recognition methods according to claim 8, which is characterized in that the sensor monitoring data are acquired from infrared biography
Sensor, ultrasonic sensor.
11. recognition methods according to claim 8, which is characterized in that the analysis Chinese herbaceous peony information, described in determination
Vehicle front includes: with the presence or absence of obstacle
Image recognition processing is carried out to the first image information；
Processing result and default template are matched, the default template be selected from default template library and with the boisterous class
Type and/or severe degree are associated；
Determine the vehicle front with the presence or absence of obstacle in conjunction with the sensor monitoring data of matching result and the vehicle front.
12. recognition methods according to claim 11, which is characterized in that before the combination matching result and the automobile
The sensor monitoring data of side determine that the vehicle front includes: with the presence or absence of obstacle
When the sensor monitoring data of the vehicle front show there are when obstacle, alternatively, before the matching result and automobile
The sensor monitoring data of side show that there are when obstacle, determine that there are obstacles for the vehicle front.
13. recognition methods according to any one of claim 1 to 12, which is characterized in that further include:
In response to the determination vehicle front, there are obstacles, issue warning information.
14. recognition methods according to any one of claim 1 to 12, which is characterized in that further include:
In response to the determination vehicle front, there are obstacles, identify the distance between the automobile and the obstacle；When the vapour
When the distance between vehicle and the obstacle are less than default safe distance, alert.
15. the identification device of Chinese herbaceous peony obstacle under a kind of bad weather characterized by comprising
Acquisition module acquires the Chinese herbaceous peony information of the vehicle front, the Chinese herbaceous peony in response to detecting that automobile is in bad weather
Information includes the first image information of the vehicle front；
Determining module determines whether the Chinese herbaceous peony information further includes other elements according to the boisterous severe degree；
Analysis module whether there is obstacle for analyzing the Chinese herbaceous peony information with the determination vehicle front.
16. identification device according to claim 15, which is characterized in that the automobile refers in bad weather: described
The low visibility of automobile local environment is in the first preset threshold.
17. identification device according to claim 16, which is characterized in that the visibility of the automobile local environment is basis
The second image information of the collected vehicle front determines in history preset time period.
18. identification device according to claim 17, which is characterized in that the first image information and second image
Information collection is from different picture pick-up devices.
19. identification device according to claim 15, which is characterized in that the analysis module includes:
First identifying processing submodule, for carrying out image recognition processing to the first image information；
First matched sub-block, for processing result and default template to match, the default template is selected from default template library
And it is associated with the boisterous type and/or severe degree；
First determines submodule, for determining the vehicle front with the presence or absence of obstacle according to matching result.
20. identification device according to claim 19, which is characterized in that the first identifying processing submodule includes:
Recognition unit, for identification object in the first image information；
Analytical unit, for analyzing the attribute information of the object recognized, to obtain the processing result, the attribute information choosing
From the weight, volume, shape of object.
21. identification device according to claim 20, which is characterized in that the default template is stored with according to historical data
The attribute information of at least one determining object and whether be obstacle judging result；First matched sub-block includes:
The attribute information of searching unit, the object for recognizing according to searches the default template；
First determination unit, for determining whether the object is obstacle according to lookup result, to obtain the matching result.
22. identification device according to claim 15, which is characterized in that the other elements of the Chinese herbaceous peony information are the vapour
The sensor monitoring data of front side.
23. identification device according to claim 22, which is characterized in that the determining module includes:
Second determines submodule, when the boisterous severe degree is lower than the second preset threshold, determines the Chinese herbaceous peony letter
Breath only includes the first image information；Alternatively,
Third determines submodule, when the boisterous severe degree is higher than second preset threshold, determines the vehicle
Preceding information further includes the sensor monitoring data.
24. identification device according to claim 22, which is characterized in that the sensor monitoring data are acquired from infrared biography
Sensor, ultrasonic sensor.
25. identification device according to claim 22, which is characterized in that the analysis module includes:
Second identifying processing submodule, for carrying out image recognition processing to the first image information；
Second matched sub-block, for processing result and default template to match, the default template is selected from default template library
And it is associated with the boisterous type and/or severe degree；
4th determines submodule, determines the vapour for the sensor monitoring data in conjunction with matching result and the vehicle front
Front side whether there is obstacle.
26. identification device according to claim 25, which is characterized in that the described 4th determines that submodule includes:
Second determination unit, when the sensor monitoring data of the vehicle front show there are when obstacle, alternatively, working as the matching
As a result show that there are when obstacle, determine that there are obstacles for the vehicle front with the sensor monitoring data of vehicle front.
27. identification device described in any one of 5 to 26 according to claim 1, which is characterized in that further include:
Warning module, in response to the determination vehicle front, there are obstacles, issue warning information.
28. identification device described in any one of 5 to 26 according to claim 1, which is characterized in that further include:
Apart from identification module, in response to the determination vehicle front, there are obstacles, identify between the automobile and the obstacle
Distance；
Alarm module, when the distance between the automobile and the obstacle are less than default safe distance, alert.
29. a kind of storage medium, is stored thereon with computer instruction, which is characterized in that the computer instruction executes when running
The step of any one of claim 1 to 14 the method.
30. a kind of terminal, including memory and processor, be stored on the memory to run on the processor
Computer instruction, which is characterized in that perform claim requires any one of 1 to 14 institute when the processor runs the computer instruction
The step of stating method.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113392804A (en) * | 2021-07-02 | 2021-09-14 | 昆明理工大学 | Multi-angle-based traffic police target data set scene construction method and system |
| CN113537036A (en) * | 2021-07-12 | 2021-10-22 | 杭州华橙软件技术有限公司 | Human shape detection method, human shape detection equipment and storage medium |
| US11718151B2 (en) * | 2018-11-20 | 2023-08-08 | Toyota Jidosha Kabushiki Kaisha | Determination device, vehicle control device, determination method and determination program |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW201009757A (en) * | 2008-08-29 | 2010-03-01 | Automotive Res & Testing Ct | Object position detecting device and method |
| DE102014204614A1 (en) * | 2014-03-12 | 2015-09-17 | Automotive Lighting Reutlingen Gmbh | Method for providing a headlight for a motor vehicle, and a lighting device for a motor vehicle |
| CN205468782U (en) * | 2016-03-21 | 2016-08-17 | 内蒙古科技大学 | Vehicle travel security alarm device and vehicle |
| CN107856671A (en) * | 2017-01-24 | 2018-03-30 | 问众智能信息科技（北京）有限公司 | A kind of method and system that road conditions identification is carried out by drive recorder |
| CN107914707A (en) * | 2017-11-17 | 2018-04-17 | 出门问问信息科技有限公司 | Anti-collision warning method, system, vehicular rear mirror and storage medium |
| US9952058B2 (en) * | 2016-08-29 | 2018-04-24 | Denso International America, Inc. | Driver visibility detection system and method for detecting driver visibility |
| CN108284793A (en) * | 2018-01-10 | 2018-07-17 | 深圳市鑫汇达机械设计有限公司 | A kind of vehicle sub-controlling unit |
-
2018
- 2018-07-20 CN CN201810802673.7A patent/CN108932503A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW201009757A (en) * | 2008-08-29 | 2010-03-01 | Automotive Res & Testing Ct | Object position detecting device and method |
| DE102014204614A1 (en) * | 2014-03-12 | 2015-09-17 | Automotive Lighting Reutlingen Gmbh | Method for providing a headlight for a motor vehicle, and a lighting device for a motor vehicle |
| EP3116750A1 (en) * | 2014-03-12 | 2017-01-18 | Automotive Lighting Reutlingen GmbH | Method for providing a headlight for a motor vehicle, and illuminating device for a motor vehicle |
| CN205468782U (en) * | 2016-03-21 | 2016-08-17 | 内蒙古科技大学 | Vehicle travel security alarm device and vehicle |
| US9952058B2 (en) * | 2016-08-29 | 2018-04-24 | Denso International America, Inc. | Driver visibility detection system and method for detecting driver visibility |
| CN107856671A (en) * | 2017-01-24 | 2018-03-30 | 问众智能信息科技（北京）有限公司 | A kind of method and system that road conditions identification is carried out by drive recorder |
| CN107914707A (en) * | 2017-11-17 | 2018-04-17 | 出门问问信息科技有限公司 | Anti-collision warning method, system, vehicular rear mirror and storage medium |
| CN108284793A (en) * | 2018-01-10 | 2018-07-17 | 深圳市鑫汇达机械设计有限公司 | A kind of vehicle sub-controlling unit |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11718151B2 (en) * | 2018-11-20 | 2023-08-08 | Toyota Jidosha Kabushiki Kaisha | Determination device, vehicle control device, determination method and determination program |
| CN113392804A (en) * | 2021-07-02 | 2021-09-14 | 昆明理工大学 | Multi-angle-based traffic police target data set scene construction method and system |
| CN113537036A (en) * | 2021-07-12 | 2021-10-22 | 杭州华橙软件技术有限公司 | Human shape detection method, human shape detection equipment and storage medium |
| CN113537036B (en) * | 2021-07-12 | 2024-02-02 | 杭州华橙软件技术有限公司 | Human shape detection method, device and storage medium |
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