CN112752067A - Target tracking method and device, electronic equipment and storage medium - Google Patents
Target tracking method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN112752067A CN112752067A CN201911047833.2A CN201911047833A CN112752067A CN 112752067 A CN112752067 A CN 112752067A CN 201911047833 A CN201911047833 A CN 201911047833A CN 112752067 A CN112752067 A CN 112752067A
- Authority
- CN
- China
- Prior art keywords
- tracking target
- target
- tracking
- road
- driving
- 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
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000012544 monitoring process Methods 0.000 claims abstract description 55
- 238000004590 computer program Methods 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 13
- 238000005516 engineering process Methods 0.000 description 10
- 238000012806 monitoring device Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
Abstract
The application provides a target tracking method, a target tracking device, an electronic device and a storage medium, wherein the method comprises the following steps: determining the current position of a tracking target and road network data comprising the current position; predicting a driving road to be passed by a tracking target according to the road network data and the current position; predicting a camera through which a tracking target passes on a driving road; and playing a monitoring picture of the camera, and identifying the tracking target by using the monitoring picture. The tracking target is identified by automatically predicting the camera, automatically playing the monitoring picture of the camera and automatically utilizing the monitoring picture, so that the tracking target is automatically tracked, and the tracking efficiency of the tracking target is improved.
Description
Technical Field
The present disclosure relates to the field of video surveillance technologies, and in particular, to a target tracking method and apparatus, an electronic device, and a storage medium.
Background
The video monitoring system is an important component of a safety precaution system widely applied to various industries and is also an important component of an intelligent traffic system. With the rapid development of computers, network transmission technology and image processing technology, the field of video monitoring is undergoing a revolution, and the video monitoring is developing from a traditional analog video system to a digital video system. The digital video monitoring system can effectively monitor the scene and record the evidence by virtue of great flexibility, and can analyze and track the target object by virtue of a video analysis technology. The collected video signals are processed and analyzed, so that the target object in the monitoring scene is identified, positioned and tracked.
In the prior art, when a tracking target is tracked, generally experienced personnel judge that a next camera of the tracking target may be shot, quickly switch a currently played camera to the next camera, and manually observe a video shot by the next camera to determine whether the next camera tracks the tracking target. This kind of mode through artifical prejudgement, switching camera, it is lower to track efficiency, often leads to the phenomenon of tracking the target and following the loss to take place.
Disclosure of Invention
The application provides a target tracking method, a target tracking device, electronic equipment and a storage medium, so that intelligent tracking of a target vehicle is achieved, and tracking efficiency of the target vehicle is improved.
In a first aspect, an embodiment of the present application provides a target tracking method, including:
determining the current position of a tracking target and road network data comprising the current position;
predicting a driving road to be passed by a tracking target according to the road network data and the current position;
predicting a camera through which a tracking target passes on a driving road;
and playing a monitoring picture of the camera, and identifying the tracking target by using the monitoring picture.
In the embodiment of the application, a driving road through which a tracking target is to pass is predicted according to the current position of the tracking target and road network data comprising the current position, then a camera through which the tracking target is to pass is predicted, a monitoring picture shot by the camera is played, and the tracking target is identified by the monitoring picture; therefore, in the embodiment of the application, the tracking efficiency of the tracked target is improved by automatically predicting the camera, automatically playing the monitoring picture of the camera and automatically identifying the tracked target by using the monitoring picture.
In one possible embodiment, the predicting a driving road to be passed by the tracking target according to the road network data and the current position comprises:
determining the driving direction of the tracking target;
and predicting a driving road which is to be passed by the tracking target along the driving direction by taking the current position as a starting point according to the road network data.
In the embodiment of the present application, the prediction of the traveling road on which the tracking target will pass is realized by predicting the traveling road on which the tracking target will pass along the traveling direction of the tracking target from the road network data, with the current position as the starting point.
In another possible embodiment, predicting a driving road to be traveled by the tracking target according to the road network data and the current position includes:
according to the road network data, predicting a driving road which is to be passed by a tracking target along a target driving direction by taking the current position as a starting point, wherein the target driving direction comprises at least one of the following:
forward direction, reverse direction, left direction, right direction.
In the embodiment of the application, the driving road to be passed by the tracking target along the target driving direction is predicted by taking the current position as the starting point according to the road network data, so that the driving road to be passed by the tracking target is predicted when the driving direction of the tracking target is uncertain.
In one possible implementation, a camera for predicting that a tracking target will pass through on a road includes:
determining the running speed of the tracking target; a camera to be photographed by a tracking target at a traveling speed with a current position as a starting point is predicted on a traveling road.
In the embodiment of the application, the tracking target is predicted to pass through the camera on the driving road by taking the current position as the starting point and taking the camera to be shot at the driving speed as the camera through which the tracking target passes on the driving road.
The following describes the target tracking apparatus, device, storage medium, and computer program product provided in this embodiment, and the contents and effects thereof may refer to the target tracking method provided in the first aspect and the optional manner of the first aspect of this embodiment, and are not described again.
In a second aspect, an embodiment of the present application provides a target tracking apparatus, including:
the system comprises a determining module, a tracking module and a tracking module, wherein the determining module is used for determining the current position of a tracking target and road network data comprising the current position;
the first prediction module is used for predicting a driving road to be passed by a tracking target according to road network data and the current position;
the second prediction module is used for predicting a camera through which the tracking target passes on the driving road;
and the processing module is used for playing the monitoring picture of the camera and identifying the tracking target by utilizing the monitoring picture.
In a possible implementation, the first prediction module is specifically configured to:
determining the driving direction of the tracking target;
and predicting a driving road which is to be passed by the tracking target along the driving direction by taking the current position as a starting point according to the road network data.
In another possible implementation, the first prediction module is specifically configured to:
according to the road network data, predicting a driving road which is to be passed by a tracking target along a target driving direction by taking the current position as a starting point, wherein the target driving direction comprises at least one of the following:
forward direction, reverse direction, left direction, right direction.
In an implementation manner, the second prediction module is specifically configured to:
determining the running speed of the tracking target;
a camera to be photographed by a tracking target at a traveling speed with a current position as a starting point is predicted on a traveling road.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
a processor;
a memory; and
a computer program;
wherein a computer program is stored in the memory and configured to be executed by the processor, the computer program comprising instructions for performing the object tracking method as described in the first aspect and the alternatives of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored, and the computer program enables a server to execute the target tracking method according to the first aspect and the alternatives of the first aspect.
In a fifth aspect, an embodiment of the present invention provides a computer program product, including: executable instructions for implementing the method of object tracking as described in the first aspect or an alternative to the first aspect.
According to the target tracking method, the target tracking device, the electronic equipment and the storage medium, the current position of the tracked target and road network data including the current position are determined; then predicting a driving road to be passed by the tracking target according to the road network data and the current position; the camera through which the tracking target passes on the driving road is predicted; and finally, playing a monitoring picture of the camera, and identifying the tracking target by using the monitoring picture. Automatically predicting the camera and automatically playing a monitoring picture of the camera; the tracking target is automatically identified by utilizing the monitoring picture, so that the tracking efficiency of the tracking target is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart diagram illustrating a target tracking method according to an embodiment of the present disclosure;
FIG. 2 is a diagram of an exemplary application scenario provided by an embodiment of the present application;
fig. 3 is a schematic structural diagram of a terminal device provided in an embodiment of the present application;
FIG. 4 is a diagram of another exemplary application scenario provided by an embodiment of the present application;
FIG. 5 is a schematic flow chart diagram illustrating a target tracking method according to another embodiment of the present application;
FIG. 6 is a schematic structural diagram of a target tracking device according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The video monitoring system is an important component of a safety precaution system widely applied to various industries and is also an important component of an intelligent traffic system. With the rapid development of computers, network transmission technologies and image processing technologies, the digital video monitoring system can effectively monitor the scene and record evidences by virtue of the great flexibility of the digital video monitoring system, and can analyze and track target objects by virtue of the video analysis technology. The collected video signals are processed and analyzed, so that the target object in the monitoring scene is identified, positioned and tracked. However, in the prior art, when tracking a tracking target, for example, a target vehicle, an experienced person usually determines a next camera that may shoot the tracking target, and quickly switches a currently playing camera to the next camera, and then manually observes a video shot by the next camera to determine whether the next camera tracks the tracking target. This kind of mode through artifical prejudgement, switching camera, it is lower to track efficiency, often leads to the phenomenon of tracking the target and following the loss to take place. In order to solve the above problem, embodiments of the present application provide a target tracking method, an apparatus, an electronic device, and a storage medium.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart of a target tracking method according to an embodiment of the present application. The method may be performed by an object tracking device, which may be implemented in software and/or hardware. Fig. 2 is an exemplary application scenario diagram provided in an embodiment of the present application, and as shown in fig. 2, the application scenario diagram includes a monitoring device 11, a server 12, and a terminal device 13, where the monitoring device 11 may be a camera, the number of the monitoring devices 11 is not limited in the embodiment of the present application, and the monitoring device 11 and the server 12 may be set in different areas according to actual needs, and the terminal device 13 and the server 12 are connected by a wired or wireless network. When the event is triggered, the terminal device 13 may acquire the current position of the tracking target and road network data including the current position, and then predict a driving road through which the tracking target will pass according to the road network data and the current position; finally, predicting a camera through which the tracking target passes on the driving road; and playing a monitoring picture of the camera, and identifying the tracking target by using the monitoring picture. In this process, the terminal device 13 may call the monitoring video of the monitoring device 11 at any time, and display the monitoring video on the display screen of the terminal device 13, so that the user can preview the tracking target.
In order to implement playing of video pictures shot by a plurality of cameras, a display screen of a terminal device may play a plurality of video pictures at the same time, fig. 3 is a schematic structural diagram of the terminal device provided in the embodiment of the present application, as shown in fig. 3, fig. 3 takes an example of playing two video pictures at the same time, and the display screen of the terminal device includes a display sub-screen 1 and a display sub-screen 2, which are respectively used for playing each video picture. In addition, the application scenario of the monitoring device is not limited in the embodiment of the application.
The terminal device can also be connected with a monitoring device. Fig. 4 is another exemplary application scenario diagram provided in the embodiment of the present application, and as shown in fig. 4, the front-end camera of the monitoring device may be a plurality of cameras 21 located on a road, and is configured to shoot a road monitoring picture, where a tracking target 22 may exist in the road monitoring picture, and transmit the shot monitoring picture to the terminal device, so as to implement playing of the monitoring picture. The application scenario of the embodiment of the present application is not limited thereto.
Based on this, the embodiment of the application provides a target tracking method, a target tracking device, an electronic device and a storage medium.
As shown in fig. 1, a target tracking method provided in an embodiment of the present application may include:
step S101: the current position of the tracking target is determined, and road network data including the current position is determined.
The method includes the steps that cameras are usually arranged on two sides of a road to monitor road conditions, the cameras can include position information of the cameras, the position information of the cameras can include geographic positions where the cameras are located and angles of videos shot by the cameras, and therefore in one possible implementation mode, the current position of a tracked target is determined, and the current position of the tracked target can be determined by the position of the camera shooting the tracked target; in another possible embodiment, the current position of the tracking target may be determined directly through a monitoring screen where the tracking target is currently located, for example, through a road identifier or a building identifier existing in the monitoring screen.
The road network data may be traffic road data, traffic junction data, or traffic network data formed by a plurality of roads, such as main roads, auxiliary roads, branch roads, and branch roads. The embodiment of the application does not limit the data form and the data type specifically contained in the road network data, the road network data can be acquired by a road network data supplier, or by downloading on the internet or from an electronic map, and the embodiment of the application does not limit the acquisition mode of the road network data. In addition, for different requirements, the road network data may be acquired in a city, a province, or a nationwide area including the current position of the tracking target, which is not limited in the embodiment of the present application, and the road network data including the current position of the tracking target is acquired to provide a basis for predicting a driving road to be passed by the tracking target.
Step S102: and predicting the driving road to be passed by the tracking target according to the road network data and the current position.
After the current position of the tracking target and the road network data including the current position are obtained, a driving road to be passed by the tracking target can be predicted according to the road network data and the current position. In one possible embodiment, the predicting a driving road to be passed by the tracking target according to the road network data and the current position comprises:
according to the road network data, predicting a driving road which is to be passed by a tracking target along a target driving direction by taking a current position as a starting point, wherein the target driving direction comprises at least one of the following: forward direction, reverse direction, left direction, right direction.
For example, the current position of the tracking target is marked in the road network data, and the driving road which the tracking target may pass through along the target driving direction is determined by taking the current position of the tracking target as a starting point. For example: judging that the current position of the tracking target is on a straight road through road network data, wherein the target driving direction may include a forward driving direction and/or a backward driving direction, and the driving road through which the tracking target passes may be a forward driving road and/or a backward driving road; for another example, if it is determined that the current position of the tracking target is at an intersection through the road network data, the target driving direction may include at least one of a forward driving direction, a backward driving direction, a leftward driving direction, and a rightward driving direction, and therefore, the driving road on which the tracking target is to pass may be any one of a forward driving road, a backward driving road, a leftward driving road, and a rightward driving road, which is not limited in this application.
Step S103: and predicting a camera which is about to pass by the tracking target on the driving road.
After the traveling road of the tracking target is predicted, in order to further realize the tracking of the tracking target, a camera through which the tracking target will pass on the traveling road may be predicted. The embodiment of the present application does not limit the specific implementation of the camera that predicts the passing of the tracking target on the driving road. In a possible implementation manner, the preset number of cameras on the driving road of the tracked target can be determined as the cameras through which the tracked target will pass on the driving road, and by determining the preset number of cameras as the cameras through which the tracked target will pass on the driving road, the problem that the tracked target shot when the number of cameras is small is not clear or the shooting time is short can be avoided, and the influence on the tracking efficiency of the tracked target when the number of cameras is too large can be reduced.
For example, if the driving road of the tracking target only has one straight road, it may be determined that the preset number of cameras on the straight road are the cameras that the tracking target will pass through on the driving road; if the driving road for tracking the target comprises a straight road and a left-turn road, at least one camera on the straight road and at least one camera on the left-turn road may be the cameras through which the tracking target will pass on the driving road. The embodiment of the application does not limit the number of the cameras, the distribution of the cameras on different driving roads and the like, and the cameras can be specifically set according to user requirements.
In order to select a camera with a higher probability of the tracking target from a plurality of cameras positioned on the traveling road as a camera through which the tracking target will pass on the traveling road, so as to improve the accuracy of predicting the camera through which the tracking target will pass on the traveling road, in another possible embodiment, the camera through which the tracking target will pass on the traveling road is predicted, and the camera includes:
determining the running speed of the tracking target; a camera to be photographed by a tracking target at a traveling speed with a current position as a starting point is predicted on a traveling road.
The method comprises the steps of determining the running speed of a tracking target, judging in a video picture shot by a camera through an image recognition technology, predicting the camera to be shot of the tracking target on a running road by taking the current position as a starting point at the running speed after determining the running speed of the tracking target.
Step S104: and playing a monitoring picture of the camera, and identifying the tracking target by using the monitoring picture.
After the camera is determined, the monitoring picture shot by the camera is played on the display screen of the terminal equipment. If the number of the cameras is one, the tracking target can be identified by playing the monitoring picture of the camera and utilizing the monitoring picture of the camera; if the number of the cameras is multiple, the monitoring images of some or all of the cameras in the multiple cameras can be played, and when the tracking target is identified by using the monitoring images, the monitoring images shot by all the cameras can be identified, and the monitoring images shot by some high-performance cameras can also be identified, which is not limited by the embodiment of the present application.
When the tracking target is a target vehicle, in order to recognize the tracking target, vehicle information of the tracking target needs to be acquired, and acquiring the vehicle information of the tracking target may be implemented by inputting vehicle information of the tracking target by a user, for example, inputting a picture or a video of the tracking target, and then recognizing the vehicle information of the tracking target from a monitoring picture by using an image recognition technology, which is not limited in the embodiment of the present application. In addition, the information content of the tracking target vehicle is not limited in the embodiments of the present application, and may be, for example, the basic feature of the tracking target or the feature information of the driver driving the tracking target. In one possible embodiment, the vehicle information includes at least one of: license plate number, vehicle type, vehicle color, driving direction, driving speed and driver image. For example, the vehicle information of the tracking target is a license plate number, a vehicle type and a vehicle color; or the vehicle information of the tracking target is the color, the driving direction, the driving speed and the like of the vehicle, and the type of the vehicle information of the tracking target is not limited in the embodiment of the application.
The embodiment of the application is not limited to a specific implementation manner of identifying the tracked target by using the monitoring screen, and in a possible implementation manner, if a suspected target identified by the camera meets a first set condition, the suspected target is determined to be the tracked target; and if the suspected target identified by the camera does not meet the first set condition, determining the artificially specified suspected target as the tracking target. When the suspected target identified by the camera meets the first set condition, the suspected target is determined to be the tracking target, so that the automatic determination of the tracking target is realized, and the tracking efficiency is improved; when the suspected target identified by the camera does not meet the first set condition, the artificially specified suspected target is determined to be the tracking target, so that the accuracy of the tracking target is improved.
Optionally, the first preset condition is that the similarity between the suspected target and the tracked target is greater than or equal to a first preset threshold. The size of the first preset threshold is not limited in the embodiment of the present application, for example, the first preset threshold is 90%.
In a possible implementation manner, if the identified suspected target does not satisfy the first setting condition, determining the tracking target according to a user instruction includes:
if the similarity between the suspected target and the tracking target is smaller than a first preset threshold and larger than or equal to a second preset threshold, recommending the suspected target to the user as the tracking target; if a tracking target changing instruction for changing the tracking target is not received within a first preset time period, determining the suspected target as the tracking target; and if the tracking target changing instruction is received within the first preset time period, determining that the target changed by the user is the tracking target.
In the embodiment of the application, when the similarity between the suspected target and the tracking target is smaller than a first preset threshold and larger than or equal to a second preset threshold, the suspected target is recommended to a user as the tracking target, and the user is waited to determine whether to use the suspected target as the tracking target by setting the preset time, so that the problem that the tracking target is not the suspected target or the suspected target is not the tracking target is effectively solved, the tracking target is confirmed through manual control of the user when the suspected target is not the tracking target, the accuracy of the tracking target is favorably improved, and the user experience can be enhanced.
And if the similarity between the suspected target and the tracking target is smaller than a second preset threshold, receiving a tracking target confirmation instruction of the user, and determining the tracking target instruction to be used for determining the tracking target. In the embodiment of the application, when the tracking target cannot be confirmed, the tracking target is determined by receiving the instruction of the user, so that the accuracy of tracking target identification can be improved, and the user experience can be enhanced.
Optionally, identifying the tracking target may further determine a suspected target with the largest similarity to the tracking target as the tracking target, which is not limited in this embodiment of the application.
In the embodiment of the application, the tracking efficiency of the tracking target is improved by automatically predicting the camera and automatically playing the monitoring picture of the camera and automatically identifying the tracking target by utilizing the monitoring picture.
In order to solve the above problem, in a possible implementation manner, the target tracking method provided in an embodiment of the present application may further include:
if the current position of the tracking target is not changed within the second preset time, stopping tracking the tracking target; or receiving a target tracking stopping instruction of the user to stop tracking the tracking target.
If the current position of the tracked target does not change within the second preset time, it indicates that the tracked target stops for the second preset time, in this case, the tracked target does not need to be tracked any more, and the tracked target can be stopped. Alternatively, the terminal device may receive a user instruction to stop tracking the target. For example, the target tracking stopping instruction of the user may be received by setting a button or a virtual key, which is not limited in the embodiment of the present application.
Optionally, fig. 5 is a schematic flowchart of a target tracking method according to another embodiment of the present application, where the method may be executed by a target tracking apparatus, and the apparatus may be implemented by software and/or hardware, for example: the apparatus may be a client or a terminal device, the terminal device may be a personal computer, a smart phone, a user terminal, a tablet computer, a wearable device, and the like, and the following describes the target tracking method with the terminal device as an execution subject, as shown in fig. 5, step S102 in the method in the embodiment of the present application, that is, predicting a driving road through which a tracking target will pass according to road network data and a current position, and the method may further include:
step S201: the traveling direction of the tracking target is determined.
The driving direction of the tracked target is determined, and may be determined through a monitoring screen where the tracked target is located, for example, the driving direction of the tracked target is determined through an image recognition technology, which is not limited in the embodiment of the present application.
Step S202: and predicting a driving road which is to be passed by the tracking target along the driving direction by taking the current position as a starting point according to the road network data.
The embodiment of the present application is not limited to a specific implementation manner of predicting a driving road to be passed by the tracking target along the driving direction with the current position as the starting point according to the road network data, and in a possible implementation manner, the current position of the tracking target and the driving direction of the tracking target may be displayed on a map in combination with the road network data and the map, and a type road to be passed by the tracking target in the driving direction may be determined. The embodiments of the present application are not limited thereto.
The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the method of the present application.
Fig. 6 is a schematic structural diagram of an object tracking apparatus provided in an embodiment of the present application, which may be implemented by software and/or hardware, for example: the device may be a client or a terminal device, and the terminal device may be a personal computer, a smart phone, a user terminal, a tablet computer, a wearable device, or the like, as shown in fig. 6, the target tracking device provided in the embodiment of the present application may include:
a determining module 51, configured to determine a current position of the tracking target and road network data including the current position;
a first prediction module 52, configured to predict a driving road on which the tracking target will pass according to the road network data and the current position;
a second prediction module 53, configured to predict a camera that a tracking target will pass through on a road;
and the processing module 54 is configured to play a monitoring picture of the camera, and identify the tracking target by using the monitoring picture.
In a possible implementation, the first prediction module 52 is specifically configured to:
determining the driving direction of the tracking target;
and predicting a driving road which is to be passed by the tracking target along the driving direction by taking the current position as a starting point according to the road network data.
In another possible implementation, the first prediction module 52 is specifically configured to:
according to the road network data, predicting a driving road which is to be passed by a tracking target along a target driving direction by taking the current position as a starting point, wherein the target driving direction comprises at least one of the following:
forward direction, reverse direction, left direction, right direction.
Optionally, the second prediction module 53 is specifically configured to:
determining the running speed of the tracking target;
a camera to be photographed by a tracking target at a traveling speed with a current position as a starting point is predicted on a traveling road.
The device embodiments provided in the present application are merely schematic, and the module division in fig. 6 is only one logic function division, and there may be another division manner in actual implementation. For example, multiple modules may be combined or may be integrated into another system. The coupling of the various modules to each other may be through interfaces that are typically electrical communication interfaces, but mechanical or other forms of interfaces are not excluded. Thus, modules described as separate components may or may not be physically separate, may be located in one place, or may be distributed in different locations on the same or different devices.
Fig. 7 is a schematic structural diagram of an electronic device provided in an embodiment of the present application, and as shown in fig. 7, the electronic device includes:
a processor 61, a memory 62, a transceiver 63 and a computer program; wherein the transceiver 63 enables data transmission with other devices, a computer program is stored in the memory 62 and configured to be executed by the processor 61, the computer program comprising instructions for performing the object tracking method described above, the content and effects of which refer to the method embodiments.
In addition, embodiments of the present application further provide a computer-readable storage medium, in which computer-executable instructions are stored, and when at least one processor of the user equipment executes the computer-executable instructions, the user equipment performs the above-mentioned various possible methods.
Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in user equipment. Of course, the processor and the storage medium may reside as discrete components in a communication device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A method of target tracking, comprising:
determining a current position of a tracking target and road network data comprising the current position;
predicting a driving road to be passed by the tracking target according to the road network data and the current position;
a camera for predicting that the tracking target will pass through on the driving road; and playing a monitoring picture of the camera, and identifying the tracking target by using the monitoring picture.
2. The method according to claim 1, wherein said predicting a road to be traveled by said tracking target based on said road network data and said current location comprises:
determining a driving direction of the tracking target;
and predicting a driving road to be passed by the tracking target along the driving direction by taking the current position as a starting point according to the road network data.
3. The method according to claim 1, wherein said predicting a road to be traveled by said tracking target based on said road network data and said current location comprises:
predicting a driving road to be passed by the tracking target along a target driving direction by taking the current position as a starting point according to the road network data, wherein the target driving direction comprises at least one of the following:
forward direction, reverse direction, left direction, right direction.
4. The method according to any one of claims 1 to 3, wherein predicting a camera through which the tracking target will pass on the travel road comprises:
determining a driving speed of the tracking target;
and predicting a camera to be shot by the tracking target on the driving road at the driving speed by taking the current position as a starting point.
5. An object tracking device, comprising:
the system comprises a determining module, a tracking module and a tracking module, wherein the determining module is used for determining the current position of a tracking target and road network data comprising the current position;
the first prediction module is used for predicting a driving road to be passed by the tracking target according to the road network data and the current position;
the second prediction module is used for predicting a camera through which the tracking target passes on the driving road;
and the processing module is used for playing the monitoring picture of the camera and identifying the tracking target by utilizing the monitoring picture.
6. The apparatus of claim 5, wherein the first prediction module is specifically configured to:
determining a driving direction of the tracking target;
and predicting a driving road to be passed by the tracking target along the driving direction by taking the current position as a starting point according to the road network data.
7. The apparatus of claim 5, wherein the first prediction module is specifically configured to:
predicting a driving road to be passed by the tracking target along a target driving direction by taking the current position as a starting point according to the road network data, wherein the target driving direction comprises at least one of the following:
forward direction, reverse direction, left direction, right direction.
8. The apparatus according to any of claims 5-7, wherein the second prediction module is specifically configured to:
determining a driving speed of the tracking target;
and predicting a camera to be shot by the tracking target on the driving road at the driving speed by taking the current position as a starting point.
9. An electronic device, comprising:
a processor;
a memory; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor, the computer program comprising instructions for performing the method of any of claims 1-4.
10. A computer-readable storage medium, characterized in that it stores a computer program that causes a server to execute the method of any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911047833.2A CN112752067A (en) | 2019-10-30 | 2019-10-30 | Target tracking method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911047833.2A CN112752067A (en) | 2019-10-30 | 2019-10-30 | Target tracking method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112752067A true CN112752067A (en) | 2021-05-04 |
Family
ID=75641152
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911047833.2A Pending CN112752067A (en) | 2019-10-30 | 2019-10-30 | Target tracking method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112752067A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114419555A (en) * | 2022-01-19 | 2022-04-29 | 广东飞达交通工程有限公司 | Road traffic target tracking method based on deep convolutional neural network |
| CN114694387A (en) * | 2022-03-31 | 2022-07-01 | 中国第一汽车股份有限公司 | Method and system for tracking automobile track |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101207638A (en) * | 2007-12-03 | 2008-06-25 | 浙江树人大学 | Method for tracking target based on prognostic wireless sensor network |
| KR20080093573A (en) * | 2007-04-17 | 2008-10-22 | 주식회사 문화방송 | Apparatus and computer-readable medium for displaying road image |
| CN104284146A (en) * | 2013-07-11 | 2015-01-14 | 松下电器产业株式会社 | Tracking assistance device, tracking assistance system and tracking assistance method |
| CN104284150A (en) * | 2014-09-23 | 2015-01-14 | 同济大学 | Smart camera autonomous coordinative tracking method and monitoring system based on road traffic monitoring |
| CN104660998A (en) * | 2015-02-16 | 2015-05-27 | 苏州阔地网络科技有限公司 | Relay tracking method and system |
| CN105306899A (en) * | 2015-10-27 | 2016-02-03 | 太原市公安局 | Monitoring video processing method and device |
| CN105450991A (en) * | 2015-11-17 | 2016-03-30 | 浙江宇视科技有限公司 | Tracking method and apparatus thereof |
| CN106162105A (en) * | 2016-08-26 | 2016-11-23 | 浙江大华技术股份有限公司 | Camera parameters control method in a kind of video monitoring system and device |
| CN106485736A (en) * | 2016-10-27 | 2017-03-08 | 深圳市道通智能航空技术有限公司 | A kind of unmanned plane panoramic vision tracking, unmanned plane and control terminal |
| CN106709436A (en) * | 2016-12-08 | 2017-05-24 | 华中师范大学 | Cross-camera suspicious pedestrian target tracking system for rail transit panoramic monitoring |
| CN106878667A (en) * | 2015-12-11 | 2017-06-20 | 深圳先进技术研究院 | Video fast track method based on road net data |
| CN106911916A (en) * | 2017-03-10 | 2017-06-30 | 北京旷视科技有限公司 | Image capturing system, apparatus and method |
| CN108257147A (en) * | 2017-12-20 | 2018-07-06 | 广东技术师范学院 | A kind of method for tracking target and device based on video sensing network |
| CN109961458A (en) * | 2017-12-26 | 2019-07-02 | 杭州海康威视系统技术有限公司 | Method for tracing, device and the computer readable storage medium of target object |
-
2019
- 2019-10-30 CN CN201911047833.2A patent/CN112752067A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20080093573A (en) * | 2007-04-17 | 2008-10-22 | 주식회사 문화방송 | Apparatus and computer-readable medium for displaying road image |
| CN101207638A (en) * | 2007-12-03 | 2008-06-25 | 浙江树人大学 | Method for tracking target based on prognostic wireless sensor network |
| CN104284146A (en) * | 2013-07-11 | 2015-01-14 | 松下电器产业株式会社 | Tracking assistance device, tracking assistance system and tracking assistance method |
| CN104284150A (en) * | 2014-09-23 | 2015-01-14 | 同济大学 | Smart camera autonomous coordinative tracking method and monitoring system based on road traffic monitoring |
| CN104660998A (en) * | 2015-02-16 | 2015-05-27 | 苏州阔地网络科技有限公司 | Relay tracking method and system |
| CN105306899A (en) * | 2015-10-27 | 2016-02-03 | 太原市公安局 | Monitoring video processing method and device |
| CN105450991A (en) * | 2015-11-17 | 2016-03-30 | 浙江宇视科技有限公司 | Tracking method and apparatus thereof |
| CN106878667A (en) * | 2015-12-11 | 2017-06-20 | 深圳先进技术研究院 | Video fast track method based on road net data |
| CN106162105A (en) * | 2016-08-26 | 2016-11-23 | 浙江大华技术股份有限公司 | Camera parameters control method in a kind of video monitoring system and device |
| CN106485736A (en) * | 2016-10-27 | 2017-03-08 | 深圳市道通智能航空技术有限公司 | A kind of unmanned plane panoramic vision tracking, unmanned plane and control terminal |
| CN106709436A (en) * | 2016-12-08 | 2017-05-24 | 华中师范大学 | Cross-camera suspicious pedestrian target tracking system for rail transit panoramic monitoring |
| CN106911916A (en) * | 2017-03-10 | 2017-06-30 | 北京旷视科技有限公司 | Image capturing system, apparatus and method |
| CN108257147A (en) * | 2017-12-20 | 2018-07-06 | 广东技术师范学院 | A kind of method for tracking target and device based on video sensing network |
| CN109961458A (en) * | 2017-12-26 | 2019-07-02 | 杭州海康威视系统技术有限公司 | Method for tracing, device and the computer readable storage medium of target object |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114419555A (en) * | 2022-01-19 | 2022-04-29 | 广东飞达交通工程有限公司 | Road traffic target tracking method based on deep convolutional neural network |
| CN114694387A (en) * | 2022-03-31 | 2022-07-01 | 中国第一汽车股份有限公司 | Method and system for tracking automobile track |
| CN114694387B (en) * | 2022-03-31 | 2023-04-28 | 中国第一汽车股份有限公司 | Method and system for tracking automobile track |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9230336B2 (en) | Video surveillance | |
| JPWO2014061342A1 (en) | Information processing system, information processing method, and program | |
| CN111091584B (en) | Target tracking method, device, equipment and storage medium | |
| CN112752067A (en) | Target tracking method and device, electronic equipment and storage medium | |
| EP3229174A1 (en) | Method for video investigation | |
| CN114764911B (en) | Obstacle information detection method, obstacle information detection device, electronic device, and storage medium | |
| CN113655930B (en) | Information publishing method, information display method and device, electronic equipment and medium | |
| CN111382695A (en) | Method and apparatus for detecting boundary points of object | |
| CN113705417A (en) | Image processing method and device, electronic equipment and computer readable storage medium | |
| CN110930437B (en) | Target tracking method and device | |
| CN112455465A (en) | Driving environment sensing method and device, electronic equipment and storage medium | |
| CN112488069B (en) | Target searching method, device and equipment | |
| CN115601738B (en) | Parking information acquisition method, device, equipment, storage medium and program product | |
| CN114913470B (en) | Event detection method and device | |
| CN115019242B (en) | Abnormal event detection method and device for traffic scene and processing equipment | |
| JPWO2020039897A1 (en) | Station monitoring system and station monitoring method | |
| CN111405203B (en) | Method and device for determining picture switching, electronic equipment and storage medium | |
| CN114802233A (en) | Vehicle control method, device, electronic device and storage medium | |
| CN112201047B (en) | Suspected vehicle foothold analysis method and device based on Flink framework | |
| CN115009301A (en) | Trajectory prediction method, trajectory prediction device, electronic equipment and storage medium | |
| CN110781797B (en) | Labeling method and device and electronic equipment | |
| KR100839590B1 (en) | System of parking control and computation method | |
| JP7107597B2 (en) | STATION MONITORING DEVICE, STATION MONITORING METHOD AND PROGRAM | |
| CN109740518B (en) | Method and device for determining object in video | |
| CN111414517B (en) | Video face analysis method, device 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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210504 |