CN113591544A - Method, system and device for tracking user through vehicle and electronic equipment - Google Patents
Method, system and device for tracking user through vehicle and electronic equipment Download PDFInfo
- Publication number
- CN113591544A CN113591544A CN202110651365.0A CN202110651365A CN113591544A CN 113591544 A CN113591544 A CN 113591544A CN 202110651365 A CN202110651365 A CN 202110651365A CN 113591544 A CN113591544 A CN 113591544A
- Authority
- CN
- China
- Prior art keywords
- target
- face
- vehicle
- face features
- features
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a method for tracking a user through a vehicle, which comprises the steps of obtaining the tracking face characteristics of the user to be tracked; pushing the tracked human face features through a vehicle networking platform; acquiring N face characteristics of N users acquired by a camera device of a target vehicle; and searching whether target face features matched with the tracking face features exist or not from the N face features. The method for tracking the user through the vehicle provided by the invention can track the target user in a larger range with higher efficiency.
Description
Technical Field
The invention relates to the technical field of vehicle networking, in particular to a method, a system, a device and electronic equipment for tracking a user through a vehicle.
Background
With the improvement of living standard of people, the popularization of automobiles is higher and higher, and various electronic devices in the automobiles are more and more, so as to better assist users in driving the automobiles, for example, the users are prompted according to road conditions or corresponding driving operations such as lane changing or braking are adopted by determining the road conditions through cameras and radars in the automobiles.
Because many cameras exist in the prior art, but the cameras have dead angles and are too high to be maintained and damaged for a long time, and the positions for better visual field placement are too high to accurately identify people, a method for tracking a target user through a vehicle camera is urgently needed.
Disclosure of Invention
The embodiment of the invention provides a method, a system and a device for tracking a user through a vehicle and electronic equipment, which can track a target user in a wider range with higher efficiency.
In a first aspect, an embodiment of the present invention provides a method for tracking a user through a vehicle, where the method includes:
acquiring the tracking face characteristics of a user to be tracked;
pushing the tracked human face features through a vehicle networking platform;
acquiring N face characteristics of N users acquired by a camera device of a target vehicle, wherein N is an integer not less than 1;
and searching whether target face features matched with the tracking face features exist or not from the N face features.
Optionally, the tracking of the facial features is pushed through a car networking platform, including:
and converting the tracked face features into face vectors, and pushing the face vectors through the Internet of vehicles platform.
Optionally, the acquiring N face features of N users collected by a camera device of the target vehicle includes:
and receiving the N face features sent by the target vehicle, wherein the N face features are obtained by performing feature extraction on user images of the N users by a processor in the target vehicle, and the user images of the N users are acquired by a camera device of the target vehicle.
Optionally, the searching for whether there is a target face feature matching the tracked face feature from the N face features includes:
and if the target face features are found from the N face features, acquiring a target position where the target face features are located, wherein the target position is the position where the target vehicle collects the target face features.
The second aspect of the embodiments of the present invention further provides a system for tracking a user by vehicles, where the system includes a vehicle networking platform and target vehicles, each of the target vehicles is provided with a camera device, and the system includes:
the Internet of vehicles platform is used for acquiring the tracking human face features of the user to be tracked and pushing the tracking human face features to the target vehicle;
the target vehicle is used for receiving the tracked human face features, acquiring N human face features of N users, and sending the N human face features to the Internet of vehicles platform, wherein N is an integer not less than 1;
and the Internet of vehicles platform is used for receiving the N face features and searching whether a target face feature matched with the tracked face feature exists in the N face features.
Optionally, the car networking platform is further configured to convert the tracked face features into face vectors, and push the face vectors through the car networking platform.
Optionally, the target vehicle is configured to collect user images of N users, and perform feature extraction on the user images of the N users through a processor in the target vehicle, so as to obtain the N face features.
Optionally, the car networking platform is configured to, when the target face features are found from the N face features, obtain the target position from upload data corresponding to the target face features uploaded by the target vehicle.
A third aspect of the embodiments of the present invention provides an electronic device, including a memory, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by one or more processors, and the one or more programs include operation instructions for performing the method for tracking a user through a vehicle, as provided in the first aspect.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the corresponding steps of the method for tracking a user by a vehicle as provided in the first aspect.
The above one or at least one technical solution in the embodiments of the present application has at least the following technical effects:
based on the technical scheme, the face tracking characteristics of the user to be tracked are pushed through the Internet of vehicles platform; acquiring N face characteristics of N users acquired by a camera device of a target vehicle; searching whether target face features matched with the tracking face features exist in the N face features; at this moment, the camera device of the target vehicle collects N face characteristics of N users, and the target vehicle can collect the N face characteristics in a large range because the target vehicle is usually in the moving process, so that after the N face characteristics are obtained, the target face characteristics are found from the N face characteristics through face matching, the tracking efficiency can be improved, and therefore the efficiency of tracking the target user in a larger range is higher.
Drawings
Fig. 1 is a system architecture diagram of a method for tracking a user through a vehicle according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a method for tracking a user via a vehicle according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The main implementation principle, the specific implementation mode and the corresponding beneficial effects of the technical scheme of the embodiment of the present application are explained in detail with reference to the accompanying drawings.
Example one
Referring to fig. 1, an embodiment of the present application provides a system for tracking a user through vehicles, where the system includes an internet of vehicles platform 10 and target vehicles 20, each of the target vehicles 20 is provided with a camera device, and the system includes:
the vehicle networking platform 10 is used for acquiring the human face tracking characteristics of a user to be tracked and pushing the human face tracking characteristics to the target vehicle 20;
the target vehicle 20 is configured to receive the tracked face features, acquire N face features of N users, and send the N face features to the internet-of-vehicles platform, where N is an integer not less than 1;
and the Internet of vehicles platform 10 is configured to receive the N face features, and search from the N face features whether a target face feature matching the tracked face feature exists.
In the embodiment of the present specification, the target vehicle 20 is all or part of the vehicle connected to the internet-of-vehicle platform 10, and the target vehicle 20 is typically a plurality of vehicles, which may be, for example, 100 ten thousand vehicles, 150 ten thousand vehicles, and the like.
Since the target vehicle 20 is all or part of the vehicles connected to the internet of vehicles platform 10, the number of the target vehicles 20 is large, a large range can be monitored, and the target vehicle 20 is usually driven by the user to move, so that the monitoring range of the target vehicle 20 is further increased.
In the embodiments of the present description, the imaging device may be a camera, a pan-tilt, or the like.
Specifically, when acquiring the tracking face features of the user to be tracked, the internet of vehicles platform 10 may perform feature extraction on the face image of the user to be tracked uploaded by the user, so as to obtain the tracking face features; after the tracked face features are obtained, the method is further configured to convert the tracked face features into face vectors, and push the face vectors to each vehicle in the target vehicle 20 through the internet of vehicles platform 10.
Specifically, when the tracked face features are converted into face vectors, the tracked face features are converted into languages which can be understood by a computer as the face vectors, for example, the tracked face features can be converted into matrix data, wherein the converted matrix data serves as the face vectors; the matrix data is then pushed to each of the target vehicles 20 via the wireless network so that each vehicle can store the converted matrix data.
In the embodiment of the present specification, after each vehicle in the target vehicle 20 receives the tracked face features, for each vehicle, the camera device in the vehicle performs face acquisition, performs feature extraction on the acquired face image to obtain face features, and sends the acquired face features to the internet of vehicles platform 10; in this manner, since each vehicle will transmit the collected facial features to the internet of vehicles platform 10, the target vehicle 20 will transmit the collected N facial features of the N users to the internet of vehicles platform 10.
In the embodiment of the present specification, N is an integer not less than 1, and in practical applications, N is typically an integer not less than 2, for example, 1000, 2000, 5000, and the like.
In this embodiment, the target vehicle 20 is configured to collect user images of N users, and perform feature extraction on the user images of the N users through a processor in the target vehicle 20 to obtain N personal face features. Specifically, when the target vehicle 20 includes a plurality of vehicles, feature extraction is performed on the captured user image by a processor in each vehicle to obtain face features extracted from the vehicle, and after the above operation is performed for each vehicle, N face features are obtained.
In another embodiment of the present disclosure, because the target vehicle 20 stores the tracked face features, the processor of the target vehicle 20 may compare all the collected face features with the tracked face features, and use all the matched face features with the matching degree with the tracked face features being greater than the set threshold as the N face features.
Specifically, when the target vehicle 20 includes a plurality of vehicles, for each vehicle, feature extraction is performed on the acquired user image by a processor in the vehicle to obtain a face feature extracted by the vehicle, the extracted face feature is compared with the tracked face feature by the processor of the vehicle to obtain a similarity between the extracted face feature and the tracked face feature, and if the similarity is greater than a set threshold, the extracted face feature is sent to the internet-of-vehicles platform 10; after each vehicle performs the above-described operations, all the facial features transmitted by the target vehicle 20 to the internet-of-vehicles platform 10 are taken as N facial features. The set threshold may be set according to actual conditions, and may be set to a value not less than 65%, for example, 65%, 75%, 80%, or the like. So, make every facial feature in the N individual face characteristics that car networking platform 10 received and the similarity of pursuing facial feature be greater than the settlement threshold value, make every facial feature in the N individual face characteristics and the matching degree of pursuing facial feature higher, can be not more than the similarity of pursuing facial feature and set for the threshold value and not upload, make the very big reduction of the quantity of the facial feature of uploading, can carry out the coarse matching in target vehicle 20's inside, carry out the fine matching in car networking platform 10, improvement matching efficiency that can be very big, make the improvement that pursuit efficiency also can be very big.
Specifically, when the target vehicle 20 includes a plurality of vehicles, for each vehicle, when the vehicle uploads facial features, upload data corresponding to the facial features needs to be uploaded to the internet of vehicles platform 10, where the upload data at least includes a position where the facial feature is collected, and may also include an identifier of the vehicle, a driving parameter, and the like.
In the embodiment of the present specification, the car networking platform 10 may obtain the similarity between each of the N face features and the tracked face feature when searching whether there is a target face feature matching the tracked face feature from the N face features, and if the similarity between a certain face feature and the tracked face feature is found to be greater than a set similarity, take the face feature having the similarity greater than the set similarity as the target face feature; if the similarity between any face feature and the tracked face feature is not found to be greater than the set similarity from the N face features, determining that the target face feature does not exist in the N face features.
Specifically, when the car networking platform 10 searches for a target face feature from N face features, the target position is obtained from the uploaded data corresponding to the target face feature uploaded by the target vehicle 20, and at this time, the target position may be added to the tracking condition to track the user to be tracked, so that the target to be tracked can be quickly tracked in a wider range.
For example, taking the target vehicle 20 as vehicles a1, a2, and A3 as an example, the vehicle networking platform 10 acquires a face feature of a user to be tracked, which is denoted by B, and pushes B to a1, a2, and A3 through a wireless network, so that B is stored in memories of a1, a2, and A3, and after receiving B, a camera is started to acquire a user image, if a1 acquires face images of 2 users and performs feature extraction, 2 person face features are obtained as B1 and B2, B1 and B2 are respectively matched with B, and if the similarity between B2 and B is greater than a set threshold, B2 and corresponding upload data C2 are uploaded to the vehicle networking platform 10; if the A2 acquires the face images of 8 users and performs feature extraction to obtain 8 personal face features, and the similarity between the face features B3 and B in the 8 personal face features is larger than a set threshold, uploading the B3 and corresponding upload data C3 to the Internet of vehicles platform 10; if the a2 acquires the face images of 12 users and performs feature extraction to obtain 12 personal face features, and the similarity between the face features B4 and B in the 12 personal face features is greater than a set threshold, the B4 and the corresponding upload data C4 are uploaded to the internet of vehicles platform 10. As such, B2, B3, and B4 received by the internet of vehicles platform 10 are made to be N facial features.
And after receiving B2, B3 and B4, the vehicle networking platform 10 obtains that the similarities between B2, B3, B4 and B are B21, B31 and B41 in sequence, if B41 is greater than the set similarity 92%, determines that B4 is a target face feature, extracts position information from C4 as a target position, adds the target position to a tracking condition, and tracks B, so as to improve the tracking efficiency.
Because a large number of human face features which are dissimilar to the tracked human face features are removed from the N human face features uploaded to the internet of vehicles platform 10, when the internet of vehicles platform 10 uses the N human face features for accurate matching, the calculation amount can be greatly reduced, and the tracking efficiency is improved.
Based on the technical scheme, the face tracking characteristics of the user to be tracked are pushed through the Internet of vehicles platform; acquiring N face characteristics of N users acquired by a camera device of a target vehicle; searching whether target face features matched with the tracking face features exist in the N face features; at this moment, the camera device of the target vehicle collects N face characteristics of N users, and the target vehicle can collect the N face characteristics in a large range because the target vehicle is usually in the moving process, so that after the N face characteristics are obtained, the target face characteristics are found from the N face characteristics through face matching, the tracking efficiency can be improved, and therefore the efficiency of tracking the target user in a larger range is higher.
Example two
Referring to fig. 2, an embodiment of the present application provides a method for tracking a user through a vehicle, the method including:
s201, acquiring tracking face features of a user to be tracked;
s202, pushing the human face tracking characteristics through a vehicle networking platform;
s203, acquiring N face characteristics of N users acquired by a camera device of the target vehicle, wherein N is an integer not less than 1;
s204, searching whether target face features matched with the tracking face features exist in the N face features.
In an optional implementation manner, the pushing the tracked facial features through a car networking platform includes:
and converting the tracked face features into face vectors, and pushing the face vectors through the Internet of vehicles platform.
In an optional implementation, the acquiring N facial features of N users captured by a camera of a target vehicle includes:
and receiving the N face features sent by the target vehicle, wherein the N face features are obtained by performing feature extraction on user images of the N users by a processor in the target vehicle, and the user images of the N users are acquired by a camera device of the target vehicle.
In an alternative embodiment, the searching for whether there is a target facial feature matching the tracked facial feature from the N facial features includes:
and if the target face features are found from the N face features, acquiring a target position where the target face features are located, wherein the target position is the position where the target vehicle collects the target face features.
FIG. 3 is a block diagram of an electronic device 800 illustrating a method for tracking a user through a vehicle, according to an exemplary embodiment. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 3, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/presentation (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing elements 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides a presentation interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to present and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for presenting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communications component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the electronic device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
A non-transitory computer readable storage medium having instructions therein which, when executed by a processor of a mobile terminal, enable the mobile terminal to perform a method of tracking a user through a vehicle, the method comprising:
acquiring the tracking face characteristics of a user to be tracked;
pushing the tracked human face features through a vehicle networking platform;
acquiring N face characteristics of N users acquired by a camera device of a target vehicle, wherein N is an integer not less than 1;
and searching whether target face features matched with the tracking face features exist or not from the N face features.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is only limited by the appended claims
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A method of tracking a user through a vehicle, the method comprising:
acquiring the tracking face characteristics of a user to be tracked;
pushing the tracked human face features through a vehicle networking platform;
acquiring N face characteristics of N users acquired by a camera device of a target vehicle, wherein N is an integer not less than 1;
and searching whether target face features matched with the tracking face features exist or not from the N face features.
2. The method of claim 1, wherein the pushing the tracked facial features through a car networking platform comprises:
and converting the tracked face features into face vectors, and pushing the face vectors through the Internet of vehicles platform.
3. The method of claim 2, wherein said obtaining N facial features of N users captured by a camera of a target vehicle comprises:
and receiving the N face features sent by the target vehicle, wherein the N face features are obtained by performing feature extraction on user images of the N users by a processor in the target vehicle, and the user images of the N users are acquired by a camera device of the target vehicle.
4. A method as recited in claim 3, wherein said finding from the N facial features whether there is a target facial feature that matches the tracked facial feature comprises:
and if the target face features are found from the N face features, acquiring a target position where the target face features are located, wherein the target position is the position where the target vehicle collects the target face features.
5. A system for tracking a user through a vehicle, the system comprising a vehicle networking platform and a target vehicle, each vehicle in the target vehicle being provided with a camera device, comprising:
the Internet of vehicles platform is used for acquiring the tracking human face features of the user to be tracked and pushing the tracking human face features to the target vehicle;
the target vehicle is used for receiving the tracked human face features, acquiring N human face features of N users, and sending the N human face features to the Internet of vehicles platform, wherein N is an integer not less than 1;
and the Internet of vehicles platform is used for receiving the N face features and searching whether a target face feature matched with the tracked face feature exists in the N face features.
6. The system of claim 5, wherein the car networking platform is further configured to convert the tracked facial features into a facial vector, and push the facial vector through the car networking platform.
7. The system of claim 6, wherein the target vehicle is configured to capture user images of N users and perform feature extraction on the user images of the N users by a processor in the target vehicle to obtain the N facial features.
8. The system of claim 7, wherein the internet of vehicles platform is configured to obtain the target location from upload data corresponding to the target facial feature uploaded by the target vehicle when the target facial feature is found from the N facial features.
9. An electronic device comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors to execute operating instructions included in the one or more programs for performing the corresponding method according to any one of claims 1 to 4.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps corresponding to the method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110651365.0A CN113591544A (en) | 2021-06-10 | 2021-06-10 | Method, system and device for tracking user through vehicle and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110651365.0A CN113591544A (en) | 2021-06-10 | 2021-06-10 | Method, system and device for tracking user through vehicle and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113591544A true CN113591544A (en) | 2021-11-02 |
Family
ID=78243868
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110651365.0A Pending CN113591544A (en) | 2021-06-10 | 2021-06-10 | Method, system and device for tracking user through vehicle and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113591544A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0527665A1 (en) * | 1991-07-19 | 1993-02-17 | Matra Cap Systemes | Board device and method for detecting and following the position of a vehicle on the road and driving-aid device applying the method |
| JP2012133411A (en) * | 2010-12-17 | 2012-07-12 | Glory Ltd | Face collation system, face collation device and face collation method |
| CN106599774A (en) * | 2016-10-31 | 2017-04-26 | 深圳市元征科技股份有限公司 | Vehicle alarm method and device |
| CN109344776A (en) * | 2018-10-09 | 2019-02-15 | 北京智行者科技有限公司 | Data processing method |
| CN109543645A (en) * | 2018-11-30 | 2019-03-29 | 北京小马智行科技有限公司 | A kind of face identification method and device |
| CN110659564A (en) * | 2019-08-12 | 2020-01-07 | 万翼科技有限公司 | Method and device for tracking users in area, computer equipment and storage medium |
| CN111611426A (en) * | 2020-04-21 | 2020-09-01 | 汉腾汽车有限公司 | Auxiliary tracking system based on combination of image recognition and Internet of vehicles |
-
2021
- 2021-06-10 CN CN202110651365.0A patent/CN113591544A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0527665A1 (en) * | 1991-07-19 | 1993-02-17 | Matra Cap Systemes | Board device and method for detecting and following the position of a vehicle on the road and driving-aid device applying the method |
| JP2012133411A (en) * | 2010-12-17 | 2012-07-12 | Glory Ltd | Face collation system, face collation device and face collation method |
| CN106599774A (en) * | 2016-10-31 | 2017-04-26 | 深圳市元征科技股份有限公司 | Vehicle alarm method and device |
| CN109344776A (en) * | 2018-10-09 | 2019-02-15 | 北京智行者科技有限公司 | Data processing method |
| CN109543645A (en) * | 2018-11-30 | 2019-03-29 | 北京小马智行科技有限公司 | A kind of face identification method and device |
| CN110659564A (en) * | 2019-08-12 | 2020-01-07 | 万翼科技有限公司 | Method and device for tracking users in area, computer equipment and storage medium |
| CN111611426A (en) * | 2020-04-21 | 2020-09-01 | 汉腾汽车有限公司 | Auxiliary tracking system based on combination of image recognition and Internet of vehicles |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107957266B (en) | Positioning method, positioning device and storage medium | |
| US9788065B2 (en) | Methods and devices for providing a video | |
| US10115019B2 (en) | Video categorization method and apparatus, and storage medium | |
| CN110557547B (en) | Lens position adjusting method and device | |
| US20170154206A1 (en) | Image processing method and apparatus | |
| JP7061191B2 (en) | Image processing methods and devices, electronic devices and storage media | |
| CN107784279B (en) | Target tracking method and device | |
| US11361586B2 (en) | Method for sending warning information, storage medium and terminal | |
| CN106409317B (en) | Method and device for extracting dream speech | |
| CN109034150B (en) | Image processing method and device | |
| CN111553372A (en) | Training image recognition network, image recognition searching method and related device | |
| CN106547850B (en) | Expression annotation method and device | |
| CN112188091B (en) | Face information identification method and device, electronic equipment and storage medium | |
| CN110909203A (en) | Video analysis method and device, electronic equipment and storage medium | |
| CN111523346A (en) | Image recognition method and device, electronic equipment and storage medium | |
| CN109034106B (en) | Face data cleaning method and device | |
| CN107122697B (en) | Automatic photo obtaining method and device and electronic equipment | |
| CN110781842A (en) | Image processing method and device, electronic equipment and storage medium | |
| CN108154090B (en) | Face recognition method and device | |
| CN107229707B (en) | Method and device for searching image | |
| CN109598183B (en) | Face authentication method, device and system | |
| CN111651627A (en) | Data processing method and device, electronic equipment and storage medium | |
| CN107239490B (en) | Method and device for naming face image and computer readable storage medium | |
| CN107948876B (en) | Method, device and medium for controlling sound box equipment | |
| CN110636377A (en) | Video processing method, device, storage medium, terminal and server |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20220107 Address after: 430000 No. n3010, 3 / F, R & D building, building n, Artificial Intelligence Science Park, Wuhan Economic and Technological Development Zone, Wuhan, Hubei Province Applicant after: Lantu Automobile Technology Co.,Ltd. Address before: 430000, No.1, Dongfeng Avenue, Wuhan Economic and Technological Development Zone, Wuhan City, Hubei Province Applicant before: Dongfeng Motor Corp. |