CN111814560B - Parking space state identification method, system, medium and equipment - Google Patents
Parking space state identification method, system, medium and equipment Download PDFInfo
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- 238000004364 calculation method Methods 0.000 claims description 8
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- 238000001514 detection method Methods 0.000 claims description 6
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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
- G06V20/586—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of parking space
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
- G08G1/127—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
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Abstract
The disclosure relates to a parking space state identification method, a parking space state identification system, a parking space state identification medium and parking space state identification equipment. The method comprises the following steps: acquiring a monitoring video shot by a roadside parking space; calculating adjacent frame differences and average frame differences of all image frames; selecting a first image frame and a second image frame corresponding to the maximum frame difference in all adjacent frame differences, and a third image frame closest to the average frame difference with the frame difference of the previous image frame; respectively calculating a first frame difference of the first image frame and the third image frame and a second frame difference of the third image frame and the second image frame; identifying a first occupancy state of the roadside parking space in the third image frame; a second occupancy state in the first image frame and/or a third occupancy state in the second image frame is determined. According to the scheme provided by the disclosure, the parking space state can be identified by utilizing the obvious difference of the parking space reflected on the frame difference of the image frames in the occupied state and the idle state and combining the parking space state in the third key image frame as a reference.
Description
Technical Field
The disclosure relates to the technical field of parking space management, in particular to a parking space state identification method, a system, a medium and equipment.
Background
In the related art, a machine vision recognition mode is generally adopted for managing roadside parking spaces to recognize parking states of the parking spaces, the roadside parking spaces are required to be continuously recognized in the mode, consumed resources are high, requirements on accuracy of models are high, and equipment cost is high.
Disclosure of Invention
In order to overcome the problems in the related art, the present disclosure provides a parking space state identification method, system, medium and device.
According to a first aspect of embodiments of the present disclosure, there is provided a parking space state identifying method, including:
acquiring a monitoring video shot by a camera for a roadside parking space in a preset time period before the current moment;
calculating adjacent frame differences and average frame differences of all image frames in the monitoring video;
selecting a first image frame and a second image frame corresponding to the maximum frame difference in all adjacent frame differences and a third image frame closest to the average frame difference with the frame difference of the previous image frame as three candidate key frames;
respectively calculating a first frame difference of the first image frame and a third image frame and a second frame difference of the third image frame and a second image frame;
identifying a first occupation state of the roadside parking space in the third image frame through a target detection algorithm;
and judging a second occupied state in the first image frame and/or a third occupied state in the second image frame of the road side parking space according to the first frame difference, the second frame difference and the first occupied state.
According to a second aspect of the embodiments of the present disclosure, there is provided a parking space status recognition system, including:
the acquisition module is used for acquiring a monitoring video shot by the camera on the road side parking space in a preset time period before the current moment;
the first calculation module is used for calculating adjacent frame differences and average frame differences of all image frames in the monitoring video;
the selection module is used for selecting a first image frame and a second image frame corresponding to the largest frame difference in all adjacent frame differences and a third image frame closest to the average frame difference with the frame difference of the previous image frame as three candidate key frames;
a second calculation module for calculating a first frame difference between the first image frame and a third image frame, and a second frame difference between the third image frame and a second image frame, respectively;
the identifying module is used for identifying a first occupied state of the roadside parking space in the third image frame through a target detection algorithm;
the first judging module is used for judging a second occupied state in the first image frame and/or a third occupied state in the second image frame of the road side parking space according to the first frame difference, the second frame difference and the first occupied state.
According to a third aspect of the embodiments of the present disclosure, there is provided a terminal device, including:
a processor; and
a memory having executable code stored thereon which, when executed by the processor, causes the processor to perform the method as described above.
According to a fourth aspect of embodiments of the present disclosure, there is provided a non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the method as described above.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects: the method has the advantages that the two key image frames with the change of the occupied state are positioned by utilizing the obvious difference of the occupied state and the idle state of the parking space in the video, the vehicle in the parking space is not required to be continuously identified, and in addition, the parking space state in the other two key image frames can be identified through the parking space state in the third key image frame serving as a reference.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be apparent from the following more particular descriptions of exemplary embodiments of the disclosure as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout exemplary embodiments of the disclosure.
FIG. 1 is a flow chart of a method for identifying parking space status according to an exemplary embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a parking space status recognition system according to an exemplary embodiment of the present disclosure;
fig. 3 is a schematic diagram of a computing device, according to an exemplary embodiment of the present disclosure.
Detailed Description
Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," "third," etc. may be used in this disclosure to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present disclosure. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present disclosure, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
The following describes in detail the technical solutions of the embodiments of the present disclosure with reference to the accompanying drawings.
Fig. 1 is a flow chart illustrating a parking space status recognition method according to an exemplary embodiment of the present disclosure.
Referring to fig. 1, the method includes:
s11, acquiring a monitoring video shot by a camera for a road side parking space in a preset time period before the current moment;
s12, calculating adjacent frame differences and average frame differences of all image frames in the monitoring video;
s13, selecting a first image frame and a second image frame corresponding to the largest frame difference in all adjacent frame differences and a third image frame closest to the average frame difference with the frame difference of the previous image frame as three candidate key frames;
s14, respectively calculating first frame differences of the first image frame and the third image frame and second frame differences of the third image frame and the second image frame;
s15, recognizing a first occupation state of the roadside parking space in the third image frame through a target detection algorithm;
s16, judging a second occupied state in the first image frame and/or a third occupied state in the second image frame of the road side parking space according to the first frame difference, the second frame difference and the first occupied state.
According to the technical scheme provided by the embodiment of the disclosure, the two key image frames with the occupied state change are positioned by utilizing the obvious difference of the parking space in the video under the occupied state and the idle state, the vehicle in the parking space is not required to be continuously identified, and in addition, the parking space states in the other two key image frames can be identified by taking the parking space state in the third key image frame as a reference.
The step S16 specifically includes:
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is occupied, the second occupied state is occupied, and the third occupied state is idle;
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is out of the set range, the second frame difference is in the set range, and the first occupied state is occupied, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is in the set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is occupied, and the third occupied state is idle.
Specifically, when the first frame difference is within the set range and the second frame difference is outside the set range, the occupation states of the first image frame and the third image frame are the same, whereas when the first frame difference is outside the set range and the second frame difference is within the set range, the occupation states of the second image frame and the third image frame are the same, so that the occupation states in the first image frame and the second image frame can be determined correspondingly.
In the above method, further comprising:
s17, identifying and marking the outline of an object in the image frame, wherein the object at least comprises a vehicle;
before step S16, the method further includes:
s18, placing the contour of the vehicle occupying the same parking space in the previous image frame of the third image frame at the same position in the third image frame, judging whether the ratio of the overlapped part of the contour of the vehicle occupying the same parking space in the previous image frame to the contour of other objects in the third image frame to the contour of the vehicle occupying the same parking space in the previous image frame is lower than a preset ratio, if so, executing the second occupied state according to the first frame difference, the second frame difference and the first occupied state, judging the roadside parking space in the first image frame or the second image frame, otherwise, not executing, and selecting a fourth image frame which is close to the average frame difference with the frame difference of the previous image frame to replace the third image frame until the ratio is lower than the preset ratio.
Because the video has objects such as past pedestrians and vehicles except vehicles in the parking space, the judgment accuracy of the occupied state is interfered, and when the ratio is smaller, the shielding degree of the interfering object to the parking space is smaller, and the video can be used for judging the occupied state, otherwise, the image frame is required to be selected again.
In the above method, further comprising:
s19, intercepting an image frame of a virtual parking space area defined in advance from the monitoring video;
step S12 specifically includes:
and calculating adjacent frame differences and average frame differences of the image frames of all the virtual parking space areas.
Specifically, in order to reduce the amount of calculation, only the image frame of the virtual parking space region defined in advance may be cut out to perform the frame difference calculation.
Corresponding to the embodiment of the application function implementation method, the disclosure further provides a parking space state identification system, terminal equipment and corresponding embodiments.
Fig. 2 is a schematic structural diagram of a parking space status recognition system according to an exemplary embodiment of the present disclosure.
Referring to fig. 2, the system includes:
the acquisition module is used for acquiring a monitoring video shot by the camera on the road side parking space in a preset time period before the current moment;
the first calculation module is used for calculating adjacent frame differences and average frame differences of all image frames in the monitoring video;
the selection module is used for selecting a first image frame and a second image frame corresponding to the largest frame difference in all adjacent frame differences and a third image frame closest to the average frame difference with the frame difference of the previous image frame as three candidate key frames;
a second calculation module for calculating a first frame difference between the first image frame and a third image frame, and a second frame difference between the third image frame and a second image frame, respectively;
the identifying module is used for identifying a first occupied state of the roadside parking space in the third image frame through a target detection algorithm;
the first judging module is used for judging a second occupied state in the first image frame and/or a third occupied state in the second image frame of the road side parking space according to the first frame difference, the second frame difference and the first occupied state.
In the above system, the first judging module is specifically configured to:
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is occupied, the second occupied state is occupied, and the third occupied state is idle;
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is out of the set range, the second frame difference is in the set range, and the first occupied state is occupied, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is in the set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is occupied, and the third occupied state is idle.
The system further comprises:
the identification marking module is used for identifying and marking the outline of an object in the image frame, wherein the object at least comprises a vehicle;
and the second judging module is used for judging whether the ratio of the overlapping part of the contour of the vehicle occupying the same parking place in the previous image frame to the contour of other objects in the third image frame to the contour of the vehicle occupying the same parking place in the previous image frame is lower than a preset ratio or not according to the first frame difference, the second frame difference and the first occupied state in the road side parking space, and/or before the third occupied state in the second image frame, placing the contour of the vehicle occupying the same parking place in the previous image frame in the third image frame, judging whether the ratio of the overlapping part of the contour of the vehicle occupying the same parking place in the previous image frame to the contour of the other objects in the third image frame to the contour of the vehicle occupying the same parking place in the previous image frame is lower than the preset ratio or not, calling the first judging module if the ratio is yes, otherwise not calling, and selecting a fourth image frame which is close to the average frame difference with the previous image frame to the third image frame to replace the third image frame until the ratio is lower than the preset ratio.
The system further comprises:
the intercepting module is used for intercepting an image frame of a virtual parking space area defined in advance from the monitoring video;
the first computing module is specifically configured to:
and calculating adjacent frame differences and average frame differences of the image frames of all the virtual parking space areas. The specific manner in which the respective modules perform the operations in the apparatus of the above embodiments has been described in detail in the embodiments related to the method, and will not be described in detail herein.
Fig. 3 is a schematic diagram of a computing device, according to an exemplary embodiment of the present disclosure.
Referring to fig. 3, a computing device 300 includes a memory 310 and a processor 320.
The processor 320 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Memory 310 may include various types of storage units, such as system memory, read Only Memory (ROM), and persistent storage. Where the ROM may store static data or instructions that are required by the processor 320 or other modules of the computer. The persistent storage may be a readable and writable storage. The persistent storage may be a non-volatile memory device that does not lose stored instructions and data even after the computer is powered down. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the persistent storage may be a removable storage device (e.g., diskette, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as dynamic random access memory. The system memory may store instructions and data that are required by some or all of the processors at runtime. Furthermore, memory 310 may include any combination of computer-readable storage media including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic disks, and/or optical disks may also be employed. In some implementations, memory 310 may include a readable and/or writable removable storage device such as a Compact Disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, dual layer DVD-ROM), a read-only blu-ray disc, an super-density optical disc, a flash memory card (e.g., SD card, min SD card, micro-SD card, etc.), a magnetic floppy disk, and so forth. The computer readable storage medium does not contain a carrier wave or an instantaneous electronic signal transmitted by wireless or wired transmission.
The memory 310 has stored thereon executable code that, when processed by the processor 320, can cause the processor 320 to perform some or all of the methods described above.
Aspects of the present disclosure have been described in detail hereinabove with reference to the accompanying drawings. In the foregoing embodiments, the descriptions of the embodiments are focused on, and for those portions of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments. Those skilled in the art will also appreciate that the acts and modules referred to in the specification are not necessarily required for the present invention. In addition, it can be understood that the steps in the method of the embodiment of the disclosure may be sequentially adjusted, combined and pruned according to actual needs, and the modules in the device of the embodiment of the disclosure may be combined, divided and pruned according to actual needs.
Furthermore, the method according to the present disclosure may also be implemented as a computer program or computer program product comprising computer program code instructions for performing part or all of the steps of the above-described method of the present disclosure.
Alternatively, the present disclosure may also be implemented as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) having stored thereon executable code (or computer program, or computer instruction code) that, when executed by a processor of an electronic device (or computing device, server, etc.), causes the processor to perform some or all of the steps of the above-described methods according to the present disclosure.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the improvement of technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (8)
1. The parking space state identification method is characterized by comprising the following steps of:
acquiring a monitoring video shot by a camera for a roadside parking space in a preset time period before the current moment;
calculating adjacent frame differences and average frame differences of all image frames in the monitoring video;
selecting a first image frame and a second image frame corresponding to the maximum frame difference in all adjacent frame differences and a third image frame closest to the average frame difference with the frame difference of the previous image frame as three candidate key frames;
respectively calculating a first frame difference of the first image frame and a third image frame and a second frame difference of the third image frame and a second image frame;
identifying a first occupation state of the roadside parking space in the third image frame through a target detection algorithm;
judging a second occupied state in the first image frame and/or a third occupied state in the second image frame of the road side parking space according to the first frame difference, the second frame difference and the first occupied state;
further comprises: identifying and marking a contour of an object in the image frame, the object including at least a vehicle;
before determining the second occupied state in the first image frame and/or the third occupied state in the second image frame according to the first frame difference, the second frame difference and the first occupied state, the method further comprises:
and placing the contour of the vehicle occupying the same parking space in the previous image frame of the third image frame at the same position in the third image frame, judging whether the ratio of the overlapped part of the contour of the vehicle occupying the same parking space in the previous image frame to the contour of other objects in the third image frame to the contour of the vehicle occupying the same parking space in the previous image frame is lower than a preset ratio, if so, executing the second occupied state of the roadside parking space in the first image frame or the second image frame according to the first frame difference, the second frame difference and the first occupied state, otherwise, not executing, and selecting a fourth image frame which is close to the average frame difference with the frame difference of the previous image frame to replace the third image frame until the ratio is lower than the preset ratio.
2. The parking space state identification method according to claim 1, wherein the determining the second occupied state in the first image frame and/or the third occupied state in the second image frame of the roadside parking space according to the first frame difference, the second frame difference and the first occupied state specifically includes:
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is occupied, the second occupied state is occupied, and the third occupied state is idle;
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is out of the set range, the second frame difference is in the set range, and the first occupied state is occupied, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is in the set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is occupied, and the third occupied state is idle.
3. The parking space state identification method according to claim 1 or 2, further comprising:
intercepting an image frame of a virtual parking space area defined in advance from the monitoring video;
the calculating the adjacent frame differences and the average frame differences of all the image frames in the monitoring video specifically includes:
and calculating adjacent frame differences and average frame differences of the image frames of all the virtual parking space areas.
4. A parking space status recognition system, comprising:
the acquisition module is used for acquiring a monitoring video shot by the camera on the road side parking space in a preset time period before the current moment;
the first calculation module is used for calculating adjacent frame differences and average frame differences of all image frames in the monitoring video;
the selection module is used for selecting a first image frame and a second image frame corresponding to the largest frame difference in all adjacent frame differences and a third image frame closest to the average frame difference with the frame difference of the previous image frame as three candidate key frames;
a second calculation module for calculating a first frame difference between the first image frame and a third image frame, and a second frame difference between the third image frame and a second image frame, respectively;
the identifying module is used for identifying a first occupied state of the roadside parking space in the third image frame through a target detection algorithm;
the first judging module is used for judging a second occupied state in the first image frame and/or a third occupied state in the second image frame of the road side parking space according to the first frame difference, the second frame difference and the first occupied state;
further comprises:
the identification marking module is used for identifying and marking the outline of an object in the image frame, wherein the object at least comprises a vehicle;
and the second judging module is used for judging whether the ratio of the overlapping part of the contour of the vehicle occupying the same parking place in the previous image frame to the contour of other objects in the third image frame to the contour of the vehicle occupying the same parking place in the previous image frame is lower than a preset ratio or not according to the first frame difference, the second frame difference and the first occupied state in the road side parking space, and/or before the third occupied state in the second image frame, placing the contour of the vehicle occupying the same parking place in the previous image frame in the third image frame, judging whether the ratio of the overlapping part of the contour of the vehicle occupying the same parking place in the previous image frame to the contour of the other objects in the third image frame to the contour of the vehicle occupying the same parking place in the previous image frame is lower than the preset ratio or not, calling the first judging module if the ratio is yes, otherwise not calling, and selecting a fourth image frame which is close to the average frame difference with the previous image frame to the third image frame to replace the third image frame until the ratio is lower than the preset ratio.
5. The parking space state recognition system according to claim 4, wherein the first judging module is specifically configured to:
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is occupied, the second occupied state is occupied, and the third occupied state is idle;
when the first frame difference is in a set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is out of the set range, the second frame difference is in the set range, and the first occupied state is occupied, the second occupied state is idle, and the third occupied state is occupied;
when the first frame difference is in the set range, the second frame difference is out of the set range, and the first occupied state is idle, the second occupied state is occupied, and the third occupied state is idle.
6. The parking spot status identification system of claim 4 or 5, further comprising:
the intercepting module is used for intercepting an image frame of a virtual parking space area defined in advance from the monitoring video;
the computing module is specifically configured to:
and calculating adjacent frame differences and average frame differences of the image frames of all the virtual parking space areas.
7. A terminal device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method of any of claims 1-3.
8. A non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the method of any of claims 1-3.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101656023A (en) * | 2009-08-26 | 2010-02-24 | 西安理工大学 | Management method of indoor car park in video monitor mode |
| CN101978696A (en) * | 2008-03-18 | 2011-02-16 | 英特尔公司 | Capturing event information using a digital video camera |
| KR101031995B1 (en) * | 2010-08-16 | 2011-05-02 | (유)티에스산업개발 | Guiding system for traffic safety in school zone |
| CN104236866A (en) * | 2014-09-01 | 2014-12-24 | 南京林业大学 | Automobile headlamp test data error correction method based on driving direction |
| JP2015185135A (en) * | 2014-03-26 | 2015-10-22 | 株式会社Ｊｖｃケンウッド | Parking recognition device, parking recognition method and program |
| JP2017001638A (en) * | 2015-06-16 | 2017-01-05 | 西日本旅客鉄道株式会社 | Train position detection system using image processing, and train position and environmental change detection system using image processing |
| CN106504580A (en) * | 2016-12-07 | 2017-03-15 | 深圳市捷顺科技实业股份有限公司 | A kind of method for detecting parking stalls and device |
| CN106677094A (en) * | 2017-03-27 | 2017-05-17 | 深圳市捷顺科技实业股份有限公司 | Barrier gate control method and device |
| CN107665599A (en) * | 2016-07-28 | 2018-02-06 | 北海和思科技有限公司 | The parking position automatic identifying method of view-based access control model detection |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW201221391A (en) * | 2010-11-26 | 2012-06-01 | Hon Hai Prec Ind Co Ltd | Vehicle and backing up method thereof |
-
2020
- 2020-06-10 CN CN202010523649.7A patent/CN111814560B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101978696A (en) * | 2008-03-18 | 2011-02-16 | 英特尔公司 | Capturing event information using a digital video camera |
| CN101656023A (en) * | 2009-08-26 | 2010-02-24 | 西安理工大学 | Management method of indoor car park in video monitor mode |
| KR101031995B1 (en) * | 2010-08-16 | 2011-05-02 | (유)티에스산업개발 | Guiding system for traffic safety in school zone |
| JP2015185135A (en) * | 2014-03-26 | 2015-10-22 | 株式会社Ｊｖｃケンウッド | Parking recognition device, parking recognition method and program |
| CN104236866A (en) * | 2014-09-01 | 2014-12-24 | 南京林业大学 | Automobile headlamp test data error correction method based on driving direction |
| JP2017001638A (en) * | 2015-06-16 | 2017-01-05 | 西日本旅客鉄道株式会社 | Train position detection system using image processing, and train position and environmental change detection system using image processing |
| CN107665599A (en) * | 2016-07-28 | 2018-02-06 | 北海和思科技有限公司 | The parking position automatic identifying method of view-based access control model detection |
| CN106504580A (en) * | 2016-12-07 | 2017-03-15 | 深圳市捷顺科技实业股份有限公司 | A kind of method for detecting parking stalls and device |
| CN106677094A (en) * | 2017-03-27 | 2017-05-17 | 深圳市捷顺科技实业股份有限公司 | Barrier gate control method and device |
Non-Patent Citations (4)
| Title |
|---|
| 基于数字图像处理技术的汽车轮廓提取;刘光蓉, 管庶安, 周红;计算机与数字工程(04);全文 * |
| 基于机器视觉的高速公路车辆停车检测;颜江峰;毛恩荣;;计算机工程与设计(16);全文 * |
| 物联模式下的停车引导***;屈俞岐;曹佳乐;杨彭晨;;物联网技术(12);第43-45页 * |
| 视觉的车位智能识别研究;杨泷迪;姜月秋;高宏伟;;沈阳理工大学学报(01);全文 * |
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