CN112810616B - Face recognition snapshot system and method for commercial vehicle - Google Patents

Face recognition snapshot system and method for commercial vehicle Download PDF

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Publication number
CN112810616B
CN112810616B CN202110042575.XA CN202110042575A CN112810616B CN 112810616 B CN112810616 B CN 112810616B CN 202110042575 A CN202110042575 A CN 202110042575A CN 112810616 B CN112810616 B CN 112810616B
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driver
face
image data
database
voice
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CN112810616A (en
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廖庆瑜
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Chongqing Suomei Intelligent Transportation Communications Services Co ltd
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Chongqing Suomei Intelligent Transportation Communications Services Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • 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
    • G06V40/172—Classification, e.g. identification
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W2040/0809—Driver authorisation; Driver identical check

Abstract

The invention relates to the field of face recognition, in particular to a face recognition snapshot system and method for commercial vehicles. The invention provides a face recognition snapshot system and a face recognition snapshot method for an operating vehicle, aiming at the problem that the existing operating vehicle recognition system can not judge whether the personnel change is in compliance when the driver reasonably changes, and the face recognition snapshot system comprises the following steps: s1, establishing a face database; s2, confirming the identity of the driver; s3, a driver change judgment step; s4, judging the compliance of the driver' S changing behavior; s5, confirming personnel change; and S6, outputting the comparison result.

Description

Face recognition snapshot system and method for commercial vehicle
Technical Field
The invention relates to the field of face recognition, in particular to a face recognition snapshot system and method for commercial vehicles.
Background
The net car booking and the taxi are one of the public travel modes, are convenient to travel, have potential safety hazards, and are concerned by all the social circles along with the frequent occurrence of riding safety events along with the rise of the net car booking in recent years. In the prior art, potential safety hazards occur in a vehicle in the process of taking a vehicle, the safety of people in the vehicle is not guaranteed, the trust of passengers on network car reservation is reduced, and the development of network car reservation is influenced; in the prior art, vehicle registration information is inconsistent with a driver, so that the vehicle operation market is disordered.
Current patent document CN110517449A discloses an intelligent wind control system for net appointment car, taxi, intelligent wind control system includes intelligent supervision terminal, real-time supervision system, alarm unit, speaker unit, audio acquisition unit, video acquisition unit and display element, and intelligent supervision terminal includes identification element, first storage unit and first contrast unit, and real-time supervision system includes human identification module, speech recognition module, threatens judgement module and danger and removes the mould. The intelligent wind control system guarantees the safety of people in the vehicle and reduces the occurrence of safety accidents by a human body posture recognition technology and combining a voice recognition technology and a face recognition technology; the intelligent wind control system has strong feasibility and can accurately and efficiently judge the dangerous case, so that certain deterrence force can be generated on lawbreakers, and the occurrence of illegal criminal events is reduced; the intelligent wind control system utilizes the facial recognition to recognize the identity of a driver in real time in the riding process, so that the condition that an illegal person drives an operating vehicle is effectively prevented.
According to the scheme, the problem that the condition that the illegal person drives the operation vehicle is effectively solved, however, in the driving of the actual operation vehicle, usually, one vehicle corresponds to a single driver, but usually, one vehicle corresponds to a plurality of drivers, and the corresponding drivers of the vehicle in a certain time period may be different.
Therefore, there is an urgent need for a face recognition snapshot system and method that can effectively recognize the compliance of a change of a driver in an operating vehicle and determine whether the change of the driver is in compliance when the driver is reasonably changed.
Disclosure of Invention
The invention provides a face recognition snapshot system and method for an operating vehicle, aiming at the problem that the existing operating vehicle recognition system cannot judge whether the personnel change is in compliance when the drivers reasonably change.
In order to solve the technical problem, the present application provides the following technical solutions:
the face recognition snapshot method for the commercial vehicle comprises the following steps:
s1, establishing a face database: collecting facial image data of all drivers, establishing a face database, and storing the facial image data of all the drivers in the face database;
s2, confirming the identity of the driver: when a vehicle is started, acquiring facial image data of a driver to obtain the facial image data of the driver, sending the facial image data of the driver to a face database, matching the facial image data of the driver with facial image data in the face database, and judging that the identity is correct and the identity is wrong if the matching is successful;
s3, driver change judging step: identifying the behavior of the driver, and determining whether to receive the personnel change information and the personnel change information sent by the operating company after judging that the driver is changed;
s4, judging the compliance of the driver' S changing behavior: if the personnel change information sent by the operation company is not received, locking the vehicle to prohibit starting; if the personnel change information is received, further confirming whether the personnel change is correct;
s5, personnel change confirmation step: if the personnel change information is received, the local terminal collects the face image data of the changed driver again, sends the collected face image data of the changed driver to the face database, matches the face image data in the face database, calls the relevant information of the driver after the matching is successful, and compares the relevant information with the received personnel change information;
s6, comparison result output step:
if the matching with the face data gathered by the face database fails, locking the vehicle to prohibit starting, and simultaneously informing a driver, a unit to which the vehicle belongs and giving an alarm;
if the face data gathered by the face database is successfully matched but is inconsistent with the received personnel change message, judging whether potential safety hazards exist, if so, locking the vehicle to prohibit starting, and simultaneously informing a driver that the person and the vehicle belong to units;
and if the face data gathered by the face database is successfully matched and is consistent with the received personnel change message, allowing the vehicle to start.
Has the advantages that: the face database is established, so that the face image data of all drivers are collected, the comparison of the face image data in the later period is facilitated, and the drivers are ensured to belong to the operators of the operation company; acquiring facial image data of a driver when the vehicle is started, sending the acquired facial image data to a face database, comparing the facial image data, judging that the identity is correct after the matching is successful, and ensuring that the driver is a driver of an operation company when the vehicle is started; judging whether the driver is changed or not, further judging whether the changed driver belongs to the operation company scheduling or not and whether the driver is in compliance change or not when judging that the driver is changed, and confirming whether the driver is changed correctly or not; acquiring changed personnel face image data, comparing the face image data with face image data in a face database, calling information of a driver after matching is successful, comparing the driver information with received personnel change information, and determining whether the change is correct; for the face image data of the changed personnel which fails to be compared, locking the vehicle, informing the driver, the affiliated unit and giving an alarm, and indicating that the change does not belong to the internal dispatching of the company; if the face matching is successful but is inconsistent with the received personnel change message, the potential safety hazard is judged to exist, the change personnel are internal drivers, but the personnel scheduling does not meet the company requirement, the vehicle is locked, and the driver and the affiliated unit of the vehicle are informed at the same time; if the facial image data are successfully matched and the facial image data are consistent with the received personnel change information, the vehicle is allowed to be started, through the steps, timely feedback supervision on vehicle driver change is achieved, the condition that illegal personnel drive the operating vehicle is effectively prevented, and meanwhile when the driver change is needed, whether the personnel change is in compliance when the driver changes reasonably can be effectively judged.
Further, S2 further includes S201, driver voice database establishment: presetting sentences, namely acquiring voice data of all drivers answering the preset sentences, establishing a voice database, and storing the voice data of all the drivers in the voice database;
s202, voice confirmation of a driver: after the driver facial image data are successfully matched, sending a voice question, carrying out voice answer of a preset sentence by the driver, collecting the voice answer, sending the voice answer of the driver to a voice database, matching the voice answer with the voice data corresponding to the driver in the voice database, and judging that the identity is correct after the matching is successful; and if the matching fails, judging the matching as an identity error.
Has the advantages that: through setting up preset sentence, gather the voice data of driver under same preset sentence, increase the degree of accuracy of judgement, and establish voice database and store all driver's voice data, after driver's facial image data match succeeds, carry out the pronunciation question, the driver carries out the pronunciation answer of predetermineeing the pronunciation, gather the pronunciation answer, match with the voice data who stores in the voice database, allow the vehicle to start under the condition of matching successfully, add the pronunciation and confirm the step on facial image discernment's basis, increase the degree of accuracy that driver judged.
Further, the step of S3 determining change of person further includes:
s301, a driver seat weight judging step: detecting the weight of the driving seat, and judging that the weight of the driving seat is changed for a person when the weight of the driving seat is changed to exceed a normal floating value;
s302, identifying and judging a driving position door: the method comprises the steps of detecting the opening and closing conditions of a door of a driving seat, carrying out voice confirmation on a driver when two behaviors of opening and closing the door of the driving seat occur, and judging that the driver changes when the voice matching of the driver fails.
Has the advantages that: by detecting the weight of the driver seat, when the weight of the driver seat changes and the change exceeds a normal floating range value, the driver of the driver seat is indicated to be replaced, and the driver can be judged to be changed; whether the driver has the action of getting off the vehicle or not is judged by detecting the opening and closing state of the driven vehicle door, the change of the driver can occur under the general condition after getting off the vehicle, and the voice recognition matching is started after the behavior of getting off the vehicle is existed, so that whether the driver is changed or not is further judged.
Further, the method also comprises the step of S7, and the safety monitoring step: and if the situation that the locking vehicle is prohibited from starting occurs in the comparison result output step, acquiring the limb actions of the driver to obtain the action image data of the driver, analyzing the amplitude range of the limb actions of the driver, and prohibiting the locking of the vehicle door and automatically opening the vehicle window after the normal action amplitude range which should occur when the driver drives normally is exceeded.
Has the advantages that: when the situation that the locked vehicle is prohibited from starting is generated, the situation that personnel change is not compliant is explained, then the limb actions of the changed driver are collected and analyzed, the movement range of the driver seat is limited, the movement range of the limb actions in normal driving actions is also limited, when the movement range of the normal limb actions is exceeded, in order to avoid further accidents, the driver is prohibited from locking the vehicle door, the vehicle window is automatically opened, the vehicle personnel and the actions are exposed, under the situation that the accidents possibly occur, the actions of the driver are exposed, passengers cannot be blocked, and the safety of the passengers is ensured.
A face identification snapshot system for a commercial vehicle, comprising:
establishing a face database module: the system comprises a face database, a face database and a display module, wherein the face database is used for collecting face image data of all drivers, establishing the face database and storing the face image data of all the drivers in the face database;
driver identity confirmation module: the system is used for acquiring the facial image data of a driver when a vehicle is started to obtain the facial image data of the driver, sending the facial image data of the driver to a face database, matching the facial image data of the driver with the facial image data in the face database, and judging that the identity is correct, the matching fails and the identity is wrong after the matching is successful;
a driver change determination module: the driver information management system is used for identifying the behavior changed by the driver, and confirming whether the driver change information sent by the operation company and the personnel change information are received or not after the driver change is judged;
the driver behavior change compliance judgment module: the method is used for locking the vehicle to prohibit starting under the condition that personnel change information sent by an operating company is not received; if the personnel change information is received, further confirming whether the personnel change is correct;
a personnel change confirmation module: if the personnel change information is received, the local terminal collects the face image data of the changed driver again, sends the collected face image data of the changed driver to the face database, matches the face image data in the face database, calls the relevant information of the driver after the matching is successful, and compares the relevant information with the received personnel change information;
a comparison result output module:
if the matching with the face data gathered by the face database fails, locking the vehicle to prohibit starting, and simultaneously informing a driver, a unit to which the vehicle belongs and giving an alarm;
if the face data gathered by the face database is successfully matched but is inconsistent with the received personnel change message, judging whether potential safety hazards exist, if so, locking the vehicle to prohibit starting, and simultaneously informing a driver that the person and the vehicle belong to units;
and if the face data gathered by the face database is successfully matched and is consistent with the received personnel change message, allowing the vehicle to start.
Has the beneficial effects that: the face database is established, so that the face image data of all drivers are collected, the later comparison of the face image data is facilitated, and the drivers are guaranteed to belong to the operators of the operation company; acquiring facial image data of a driver when the vehicle is started, sending the acquired facial image data to a face database, comparing the facial image data, allowing the vehicle to be started after matching is successful, and ensuring that the driver is a driver of the operation company when the vehicle is started; judging whether the driver is changed or not, further judging whether the changed driver belongs to the operation company scheduling or not and whether the driver is in compliance change or not when judging that the driver is changed, and confirming whether the driver is changed correctly or not; acquiring changed personnel face image data, comparing the face image data with face image data in a face database, calling information of a driver after matching is successful, comparing the driver information with received personnel change information, and determining whether the change is correct; for the face image data of the change personnel which fails to be compared, locking the vehicle, informing a driver of the change personnel and the affiliated unit, and giving an alarm, wherein the change is not in the internal dispatching of the company; if the face matching is successful but is inconsistent with the received personnel change message, the potential safety hazard is judged to exist, the changed personnel are internal drivers, but the personnel scheduling does not meet the requirements of the company, and the vehicle is locked and the driver and the unit to which the vehicle belongs are informed at the same time; if the facial image data are successfully matched and the facial image data are consistent with the received personnel change information, the vehicle is allowed to be started, through the steps, timely feedback supervision on personnel changes of a vehicle driver is achieved, the condition that illegal personnel drive the operating vehicle is effectively prevented, and meanwhile when the driver needs to change, whether the personnel changes are in compliance when the driver reasonably changes can be effectively judged.
Further, the method also comprises a driver voice database establishing submodule: the voice database is used for setting preset sentences, collecting voice data of all drivers answering the preset sentences, establishing a voice database and storing the voice data of all the drivers in the voice database;
the voice confirmation submodule of the driver: after the driver facial image data are successfully matched, sending a voice question, carrying out voice answer of a preset sentence by the driver, collecting the voice answer, sending the voice answer of the driver to a voice database, matching the voice answer with the voice data corresponding to the driver in the voice database, and judging that the identity is correct after the matching is successful; and if the matching fails, judging the matching as an identity error.
Has the advantages that: through setting up preset sentence, gather the voice data of navigating mate under same preset sentence, increase the degree of accuracy of judgement, and establish voice database and store all navigating mate's voice data, after driver face image data match succeeds, carry out the pronunciation and ask questions, the driver carries out the pronunciation answer of predetermineeing the pronunciation, gather the pronunciation answer, match with the voice data who stores in the voice database, allow the vehicle to start under the successful condition of matching, add the pronunciation and confirm the step on facial image recognition's basis, increase the degree of accuracy that the navigating mate judged.
Further, the personnel change judging module further comprises:
driver seat weight judgment submodule: the weight of the driver seat is detected, and when the weight of the driver seat changes beyond a normal floating value, the driver seat is judged to be changed;
driver's seat door discernment judges submodule: the voice recognition device is used for detecting the opening and closing conditions of the door of the driving seat, carrying out voice confirmation on a driver when two behaviors of opening and closing the door of the driving seat occur, and judging that the driver changes when the voice matching of the driver fails.
Has the advantages that: by detecting the weight of the driver seat, when the weight of the driver seat changes and the change exceeds a normal floating range value, the driver of the driver seat is indicated to be replaced, and the driver can be judged to be changed; whether a driver of a driver seat has the action of getting off is judged by detecting the opening and closing state of a driven vehicle door, personnel change may occur under the ordinary condition after getting off, voice recognition matching is started after the driver has the action of getting off, and whether the driver is changed during getting off is further judged.
Further, still include the safety monitoring module: and if the situation that the locking vehicle is prohibited from starting occurs in the comparison result output step, acquiring the limb actions of the driver to obtain the action image data of the driver, analyzing the amplitude range of the limb actions of the driver, and prohibiting the locking of the vehicle door and automatically opening the vehicle window after the normal action amplitude range which should occur when the driver drives normally is exceeded.
Has the advantages that: when the situation that the locked vehicle is prohibited from being started appears, the situation that personnel change is not compliant is shown, then the limb actions of the changed driver are collected and analyzed, the movement range of a driver seat is limited, the movement range of the limb actions in normal driving actions is also limited, and when the movement range of the normal limb actions is exceeded, in order to avoid further accidents, the driver is prohibited from locking a vehicle door, meanwhile, a vehicle window is automatically opened, the vehicle personnel and the actions are exposed, and under the situation that the accidents possibly occur, the actions of the driver are exposed, the actions of passengers cannot be blocked, and the safety of the passengers is ensured.
Drawings
Fig. 1 is a flowchart of a face recognition snapshot method for a commercial vehicle according to the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
example one
A face recognition snapshot method for a commercial vehicle, as shown in fig. 1, includes the following steps:
s1, establishing a face database: collecting facial image data of all drivers, establishing a face database, and storing the facial image data of all the drivers in the face database;
s2, confirming the identity of the driver: when a vehicle is started, acquiring facial image data of a driver to obtain the facial image data of the driver, sending the facial image data of the driver to a face database, matching the facial image data of the driver with the facial image data in the face database, judging that the identity is correct after the matching is successful, judging that the matching is failed, and judging that the identity is wrong;
s201, establishing a voice database of a driver: presetting sentences, collecting voice data of all drivers answering the preset sentences, establishing a voice database, and storing the voice data of all the drivers in the voice database;
s202, voice confirmation of a driver: after the driver facial image data are successfully matched, sending a voice question, carrying out voice answer of a preset sentence by the driver, collecting the voice answer, sending the voice answer of the driver to a voice database, matching the voice answer with the voice data corresponding to the driver in the voice database, and judging that the identity is correct after the matching is successful; and if the matching fails, judging the matching as an identity error.
S3, driver change judging step: identifying the behavior of the driver, and determining whether to receive the personnel change information and the personnel change information sent by the operating company after judging that the driver is changed;
s301, a driver seat weight judging step: detecting the weight of the driving seat, and judging that the weight of the driving seat is changed for a person when the weight of the driving seat is changed to exceed a normal floating value;
s302, identifying and judging a driving position door: the method comprises the steps of detecting the opening and closing conditions of a door of a driving seat, carrying out voice confirmation on a driver when two behaviors of opening and closing the door of the driving seat occur, and judging that the driver changes when the voice matching of the driver fails.
S4, judging the compliance of the driver' S changing behavior: if the personnel change information sent by the operation company is not received, locking the vehicle to prohibit starting; if the personnel change information is received, further confirming whether the personnel change is correct;
s5, personnel change confirmation step: if the personnel change information is received, the local terminal collects the face image data of the changed driver again, sends the collected face image data of the changed driver to the face database, matches the face image data in the face database, calls the relevant information of the driver after the matching is successful, and compares the relevant information with the received personnel change information;
s6, comparison result output step:
if the identity is judged to be wrong, the vehicle is locked to be prohibited from starting, and meanwhile, the driver is informed, the unit to which the vehicle belongs and an alarm are given;
if the identity is judged to be correct, but the identity is inconsistent with the received personnel change message, judging whether potential safety hazards exist, if so, locking the vehicle to prohibit starting, and simultaneously informing a driver of the person and the unit to which the vehicle belongs;
if the identity is judged to be correct and the identity is consistent with the received personnel change message, the vehicle is allowed to start.
S7, safety monitoring: if the situation that the locking vehicle is prohibited from starting occurs in the comparison result output step, acquiring limb actions of a driver to obtain action image data of the driver, analyzing the amplitude range of the limb actions of the driver, and prohibiting the locking of a vehicle door and automatically opening a vehicle window after the amplitude range of the normal actions which should occur when the driver drives normally is exceeded; the range exceeding the normal action amplitude that the driver should appear in normal driving in this embodiment means that the arm lifts over the neck and the body leaves the driving position, and the extraction of human body key points in the prior art is adopted to recognize the limb action of the driver.
A face identification snapshot system for a commercial vehicle, comprising the following modules:
establishing a face database module: the system comprises a face database, a face image database and a database server, wherein the face image database is used for collecting face image data of all drivers, establishing the face database and storing the face image data of all the drivers in the face database;
driver identity confirmation module: the system comprises a face database, a driver image database, a face image database and a server, wherein the face image database is used for acquiring the face image data of a driver when the vehicle is started to obtain the face image data of the driver, the face image data of the driver is sent to the face database to be matched with the face image data in the face database, and after the matching is successful, the identity is judged to be correct, the matching is failed, and the identity is judged to be wrong;
a driver voice database establishing submodule: the voice database is used for setting preset sentences, collecting voice data of all drivers answering the preset sentences, establishing a voice database and storing the voice data of all the drivers in the voice database;
the voice confirmation submodule of the driver: after the driver facial image data are successfully matched, sending a voice question, carrying out voice answer of a preset sentence by the driver, collecting the voice answer, sending the voice answer of the driver to a voice database, matching the voice answer with the voice data corresponding to the driver in the voice database, and judging that the identity is correct after the matching is successful; and if the matching fails, judging the matching as an identity error.
A driver change determination module: the driver information management system is used for identifying the behavior changed by the driver, and confirming whether the driver change information sent by the operation company and the personnel change information are received or not after the driver change is judged;
driver seat weight judgment submodule: the weight of the driver seat is detected, and when the weight of the driver seat changes beyond a normal floating value, the driver seat is judged to be changed;
the driver seat door identification and judgment submodule comprises: the voice recognition device is used for detecting the opening and closing conditions of the door of the driving seat, carrying out voice confirmation on a driver when two behaviors of opening and closing the door of the driving seat occur, and judging that the driver changes when the voice matching of the driver fails.
The driver behavior change compliance judgment module: the method is used for locking the vehicle to prohibit starting under the condition that personnel change information sent by an operation company is not received; if the personnel change information is received, further confirming whether the personnel change is correct;
a personnel change confirmation module: if the personnel change information is received, the local terminal collects the face image data of the changed driver again, sends the collected face image data of the changed driver to the face database, matches the face image data in the face database, calls the relevant information of the driver after the matching is successful, and compares the relevant information with the received personnel change information;
a comparison result output module:
if the identity is judged to be wrong, the vehicle is locked to be prohibited from starting, and meanwhile, the driver is informed, the unit to which the vehicle belongs and an alarm are given;
if the identity is judged to be correct, but the identity is inconsistent with the received personnel change message, judging whether potential safety hazards exist, if so, locking the vehicle to prohibit starting, and simultaneously informing a driver of the person and the unit to which the vehicle belongs;
if the identity is judged to be correct and the identity is consistent with the received personnel change message, the vehicle is allowed to start.
The safety monitoring module: if the situation that the vehicle is locked and the vehicle is prohibited from being started appears in the comparison result output step, collecting the limb actions of the driver to obtain action image data of the driver, analyzing the amplitude range of the limb actions of the driver, prohibiting the locking of the vehicle door and automatically opening the vehicle window when the amplitude range exceeds the normal action amplitude range which the driver should normally drive; the range exceeding the normal action range which should appear when the driver drives normally refers to that the arms lift the neck and the body leave the driving position, the key point positions of the head, the neck, the shoulders, the elbows, the hands, the hips, the knees and the feet of the driver are identified by adopting the spacious prior art, and the identification of the limb action is realized by connecting the key point.
Example two
Compared with the first embodiment, the first embodiment is different in that the first embodiment further comprises a database updating module, wherein the database updating module is used for controlling the driver identity confirmation module to continuously acquire a plurality of groups of image data to be updated of the driver after the driver identity confirmation module successfully matches the driver face image data with the face image data in the face database, then the database updating module is used for screening an image with the highest definition as temporary updated image data according to whether the image data to be updated is focused or not, then the image data is updated to the face database, and the face data and dressing data of the driver are extracted as identification feature points. When recognition is carried out again today, temporary updating image data is preferentially selected to be compared with collected facial image data of a driver, and recognition characteristic points can be added for recognition during comparison. And deleting the temporary update image data in the face database by the database update module after the time is the next day and the engine is cooled to normal temperature.
By adopting the mode, for the driver, after the driver is successfully recognized for the first time, the face database updates the face data and the wearing data of the driver today as the recognition feature points. Get off the bus temporarily at the driver, get into the vehicle again and carry out secondary even when cubic discernment, promotion face identification speed that can be very big guarantees user's experience with the car.
After a driver enters a vehicle for the first time, because the vehicle is usually required to be simply heated after a cold vehicle is started, the time cannot be directly ignored, and therefore, in order to ensure the accuracy of face recognition, the user can accept the waiting time. However, if the user is merely parked temporarily (for example, getting off the car to buy bottles of water), the user experience will be impaired if the user spends more time to identify again. Therefore, in the embodiment, the time is increased for the next day, and the engine is cooled to the normal temperature, the temporarily updated image data is deleted, the waiting time of the hot car is fully utilized, and the user experience in the normal use process is ensured.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.

Claims (8)

1. The face recognition snapshot method for the commercial vehicle is characterized by comprising the following steps of:
s1, establishing a face database: collecting facial image data of all drivers, establishing a face database, and storing the facial image data of all the drivers in the face database;
s2, confirming the identity of the driver: when a vehicle is started, acquiring facial image data of a driver to obtain the facial image data of the driver, sending the facial image data of the driver to a face database, matching the facial image data of the driver with facial image data in the face database, and judging that the identity is correct and the identity is wrong if the matching is successful;
after the driver face image data is successfully matched with the face image data in the face database, controlling a driver identity confirmation module to continuously acquire a plurality of groups of image data to be updated of the driver, screening an image with the highest definition according to image focusing of the image data to be updated to serve as temporary updated image data, updating the temporary updated image data into the face database, and extracting the face data and dressing data of the driver to serve as identification feature points; when recognition is carried out again on the same day, the temporary updating image data is preferentially selected to be compared with the collected facial image data of the driver, and the recognition characteristic points are added for recognition during comparison;
s3, driver change judging step: identifying the behavior of the driver, and determining whether to receive the personnel change information sent by the operating company after judging that the driver is changed;
s4, a driver behavior change compliance judgment step: if the personnel change information sent by the operating company is not received, locking the vehicle to prohibit starting; if the personnel change information is received, further confirming whether the personnel change is correct;
s5, personnel change confirmation step: if the personnel change information is received, the local terminal collects the face image data of the changed driver again, sends the collected face image data of the changed driver to the face database, matches the face image data in the face database, calls the relevant information of the driver after the matching is successful, and compares the relevant information with the received personnel change information;
s6, comparison result output step:
if the matching with the face data gathered by the face database fails, locking the vehicle to prohibit starting, and simultaneously informing a driver, a unit to which the vehicle belongs and giving an alarm;
if the face data gathered by the face database is successfully matched but is inconsistent with the received personnel change information, judging whether potential safety hazards exist, if so, locking the vehicle to prohibit starting, and simultaneously informing a driver that the person and the vehicle belong to units;
and if the face data gathered by the face database is successfully matched and is consistent with the received personnel change information, allowing the vehicle to start.
2. The face recognition snapshot method for commercial vehicles according to claim 1, wherein: s2 further comprises the following steps of S201, driver voice database establishment: presetting sentences, namely acquiring voice data of all drivers answering the preset sentences, establishing a voice database, and storing the voice data of all the drivers in the voice database;
s202, voice confirmation of a driver: after the driver facial image data are successfully matched, sending a voice question, carrying out voice answer of a preset sentence by the driver, collecting the voice answer, sending the voice answer of the driver to a voice database, matching the voice answer with the voice data corresponding to the driver in the voice database, and judging that the identity is correct after the matching is successful; and if the matching fails, judging the matching as an identity error.
3. The face recognition snapshot method for commercial vehicles according to claim 1, wherein: s3, the driver change determining step further includes:
s301, a driver seat weight judging step: detecting the weight of the driving seat, and judging that the weight of the driving seat is changed for a person when the weight of the driving seat is changed to exceed a normal floating value;
s302, identifying and judging a driving position door: the method comprises the steps of detecting the opening and closing conditions of a door of a driving seat, carrying out voice confirmation on a driver when two behaviors of opening and closing the door of the driving seat occur, and judging that the driver changes when the voice matching of the driver fails.
4. The face recognition snapshot method for commercial vehicles according to claim 1, wherein: further comprising S7, safety monitoring step: if the situation that the vehicle is locked and the vehicle is prohibited from being started appears in the comparison result output step, collecting the limb actions of the driver, obtaining the action image data of the driver, analyzing the amplitude range of the limb actions of the driver, prohibiting the locking of the vehicle door and automatically opening the vehicle window when the amplitude range exceeds the normal action amplitude range which the driver should normally drive.
5. A face identification snapshot system for a commercial vehicle, comprising the steps of:
establishing a face database module: the system comprises a face database, a face database and a display module, wherein the face database is used for collecting face image data of all drivers, establishing the face database and storing the face image data of all the drivers in the face database;
driver identity confirmation module: the system comprises a face database, a driver image database, a face image database and a server, wherein the face image database is used for acquiring the face image data of a driver when the vehicle is started to obtain the face image data of the driver, the face image data of the driver is sent to the face database to be matched with the face image data in the face database, and after the matching is successful, the identity is judged to be correct, the matching is failed, and the identity is judged to be wrong;
driver change judgment module: the driver information management system is used for identifying the behavior changed by the driver, and confirming whether the driver change information sent by the operation company is received or not after the driver is judged to be changed;
the driver change behavior compliance judgment module: the method is used for locking the vehicle to prohibit starting under the condition that personnel change information sent by an operating company is not received; if the personnel change information is received, further confirming whether the personnel change is correct;
a personnel change confirmation module: if the personnel change information is received, the local terminal collects the face image data of the changed driver again, sends the collected face image data of the changed driver to the face database, matches the face image data in the face database, calls the relevant information of the driver after the matching is successful, and compares the relevant information with the received personnel change information;
a comparison result output module:
if the matching with the face data gathered by the face database fails, locking the vehicle to prohibit starting, and simultaneously informing a driver, a unit to which the vehicle belongs and giving an alarm;
if the face data gathered by the face database is successfully matched but is inconsistent with the received personnel change information, judging whether potential safety hazards exist, if so, locking the vehicle to prohibit starting, and simultaneously informing a driver of the person and the unit to which the vehicle belongs;
if the face data gathered by the face database is successfully matched and is consistent with the received personnel change information, allowing the vehicle to start;
the system comprises a driver identity confirmation module, a database updating module and a data processing module, wherein the driver identity confirmation module is used for controlling the driver identity confirmation module to continuously acquire a plurality of groups of image data to be updated of a driver after successfully matching the driver face image data with the face image data in a face database; when recognition is carried out again on the same day, the temporary updating image data is preferentially selected to be compared with the collected facial image data of the driver, and the recognition characteristic points are added for recognition during comparison.
6. The face recognition snapshot system for commercial vehicles of claim 5, wherein: the method also comprises a driver voice database establishing submodule: the voice database is used for setting a preset sentence, collecting voice data of all drivers answering the preset sentence, establishing a voice database, and storing the voice data of all the drivers in the voice database;
the voice confirmation submodule of the driver: after the driver facial image data are successfully matched, sending a voice question, carrying out voice answer of a preset sentence by the driver, collecting the voice answer, sending the voice answer of the driver to a voice database, matching the voice answer with the voice data corresponding to the driver in the voice database, and judging that the identity is correct after the matching is successful; and if the matching fails, judging the identity is wrong.
7. The face recognition snapshot system for commercial vehicles of claim 5, wherein: the driver change judgment module further comprises:
driver seat weight judgment submodule: the weight of the driver seat is detected, and when the weight of the driver seat changes beyond a normal floating value, the driver seat is judged to be changed;
driver's seat door discernment judges submodule: the voice recognition system is used for detecting the opening and closing conditions of the door of the driving seat, performing voice confirmation on a driver when two behaviors of opening and closing the door of the driving seat occur, and judging that the driver changes when the voice matching of the driver fails.
8. The face recognition snapshot system for commercial vehicles of claim 5, wherein: still include the safety monitoring module: and if the situation that the locking vehicle is prohibited from starting occurs in the comparison result output step, acquiring the limb actions of the driver to obtain the action image data of the driver, analyzing the amplitude range of the limb actions of the driver, and prohibiting the locking of the vehicle door and automatically opening the vehicle window after the normal action amplitude range which should occur when the driver drives normally is exceeded.
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