CN110738858A - Camera image processing method, coder-decoder and storage device - Google Patents
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Abstract
The invention discloses an camera image processing method, a coder-decoder and a storage device, wherein the camera image processing method comprises the steps of obtaining a camera image, determining whether a person and a vehicle exist in the camera image at the same time, detecting the speed of the person and the vehicle when the person and the vehicle exist in the camera image at the same time, determining the faster and the slower of the speed of the person and the speed of the vehicle, calling an identification image program corresponding to the faster to perform image identification, and calling an identification image program corresponding to the slower to perform image identification.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an camera image processing method, a codec, and a storage device.
Background
With the popularization of the intelligent identification function of the cameras, more and more cameras need to have the capabilities of face identification, license plate identification and customized identification in practical application, the cameras can also work normally at night and need light supplement for the monitored area of the cameras, and infrared light or white light is used conventionally.
Disclosure of Invention
The application provides camera image processing methods, codec and storage device for all intelligent cameras, through judging people and the speed of car, select the order of calling the image procedure, carry out accurate discernment to face in the image and license plate, not only can guarantee the recognition function of discernment class camera, promote recognition efficiency, compromise the recognition effect of a plurality of scenes and the object of waiting to discern of different reflectivity simultaneously.
In order to solve the technical problems, technical solutions adopted by the application are to provide camera image processing methods, including:
acquiring a camera image;
determining whether a person and a vehicle are present in the camera image at the same time;
detecting the speed of the person and the vehicle when the person and the vehicle exist in the camera image at the same time;
judging whether the speed of the person is greater than the speed of the vehicle;
determining the faster and slower of the speed of the person and the speed of the vehicle;
and calling the identification image program corresponding to the faster person to perform image identification, and calling the identification image program corresponding to the slower person to perform image identification.
To solve the above technical problems, another technical solutions adopted by the present application are to provide codecs including a processor and a memory coupled to the processor, where the memory stores program instructions for implementing the camera image processing method, and the processor is configured to execute the program instructions stored in the memory to process a camera image.
To solve the above technical problems, another technical solutions adopted by the present application are to provide storage devices storing program files capable of implementing the camera image processing method.
The beneficial effect of this application is: through the speed of detecting people and car, select the order of transferring the image procedure, carry out accurate discernment to people's face in the image and license plate, not only can guarantee the recognition function of discernment class camera, promote recognition efficiency, compromise the recognition effect of the object of waiting to discern of a plurality of scenes and different reflectivities simultaneously.
Drawings
FIG. 1 is a schematic flow chart of a camera image processing method according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of a camera image processing method according to a second embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a camera image processing apparatus according to an th embodiment of the present invention;
fig. 4 is a schematic configuration diagram of a camera image processing apparatus according to a second embodiment of the present invention;
FIG. 5 is a block diagram of a codec according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a memory device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, rather than all embodiments.
In the present application, the terms "", "second", "third" are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated, whereby the features defined as "", "second", "third" may explicitly or implicitly include at least of these features.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least embodiments of the application.
FIG. 1 is a schematic flow chart diagram of a camera image processing method according to an embodiment of the present invention, it should be noted that the method of the present invention is not limited to the flow chart shown in FIG. 1 if substantially the same results are obtained, and as shown in FIG. 1, the method includes the steps of:
step S101: a camera image is acquired.
In step S101, the camera image may be a video image or a single frame image.
Step S102: it is determined whether a person and a vehicle are simultaneously present in the camera image.
In step S102, there are included collecting picture data in a camera image, determining whether a person and a vehicle are simultaneously present in the camera image based on the picture data, in this embodiment, the picture data in the camera image includes contour data of the person and contour data of the vehicle, determining whether the person and the vehicle are simultaneously present in the camera image based on the picture data, in embodiment, determining whether the person and the vehicle are simultaneously present in the camera image based on the picture data and a preset contour, in which the picture data is compared with a preset vehicle type, in which the presence of the vehicle in the camera image is detected when the contour corresponding to a preset vehicle type is present in the picture data, in which the picture data is compared with the preset vehicle type, in which the presence of the person and the vehicle is detected when the contour corresponding to the preset vehicle type is present in the picture data, in which the presence of the person in the camera image is detected, in which the picture data is compared with the preset vehicle type, in which the presence of the person and the vehicle is detected in the picture data, in which the camera image is output, in which the picture data is output as a result of the presence of the person and the vehicle image when the presence of the person and the vehicle are detected.
Step S103: when a person and a vehicle are simultaneously present in the camera image, the speeds of the person and the vehicle are detected.
In step S103, the step of detecting the speeds of the person and the vehicle includes: acquiring multiple frames of camera images, wherein people and vehicles exist in the camera images; selecting two frames of camera images, recording the shooting time of the two frames of camera images, and respectively calculating the displacement of a person and the displacement of a vehicle; the speed of the person and the speed of the vehicle are calculated from the photographing time, the displacement amount of the person, and the displacement amount of the vehicle, respectively. The speed of the person is the ratio of the displacement of the person to the shooting time difference of the two frames of camera images, and the speed of the vehicle is the ratio of the displacement of the vehicle to the shooting time difference of the two frames of camera images.
Step S104: the faster and slower of the speed of the person and the speed of the vehicle are determined.
In step S104, the person and the vehicle coming from the camera appear within the shooting range of the camera earlier as the speed is higher.
Step S105: and calling the identification image program corresponding to the faster person to perform image identification, and calling the identification image program corresponding to the slower person to perform image identification.
In step S105, the human-corresponding recognition image program performs face recognition, and the vehicle-corresponding recognition image program performs license plate recognition. And comparing the speed of the person with the speed of the vehicle, and calling the identification image program corresponding to the person and then calling the identification image program corresponding to the vehicle when the speed of the person is greater than the speed of the vehicle. When the speed of the vehicle is higher than that of the person, the identification image program corresponding to the vehicle is called first, and then the identification image program corresponding to the person is called. When the speed of the person is equal to that of the vehicle, the identification image program corresponding to the vehicle is called preferentially, and then the identification image program corresponding to the person is called. In this embodiment, when the speed of the person outside the vehicle is equal to the speed of the vehicle, the identification image program corresponding to the vehicle is called with priority, and the identification image program corresponding to the person is called again.
The camera image processing method of the embodiment of the invention is applicable to all intelligent cameras, and can accurately identify faces and license plates in images respectively by judging the speeds of people and vehicles and selecting the sequence of calling image programs, thereby not only ensuring the identification function of identification cameras and improving the identification efficiency, but also considering the identification effects of a plurality of scenes and objects to be identified with different reflectivities.
Fig. 2 is a flowchart illustrating a camera image processing method according to a second embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 2 if the results are substantially the same. As shown in fig. 2, the method comprises the steps of:
step S201: a camera image is acquired.
Step S201 in this embodiment is similar to step S101 in fig. 1, and is not described herein again.
Step S202: and presetting an image program, wherein the image program comprises a license plate recognition image program, a face recognition image program and a general image program.
In step S202, an image program is preset according to a scene, wherein the scene refers to a daytime scene or a nighttime scene, and a ball-grabbing linkage scheme, a single gun scheme or a single ball scheme is adopted, and the image program is preset according to the steps of: adjusting camera data according to the reflection characteristics of the human face or the human body, wherein the camera data when the human face information can be recognized is a preset human face recognition image program; adjusting camera data according to the reflection characteristic of the license plate, wherein the camera data when the license plate information can be identified is a preset license plate identification image program; and adjusting the camera data according to the environment, wherein the camera data when the camera data is adjusted to be capable of identifying the outlines of the people and the vehicle is a preset general image program.
The preset face recognition image program, the preset license plate recognition image program and the preset general image program all comprise an aperture control mode or parameter, a fast control mode or parameter, a gain control mode or parameter and a fill-in light intensity control mode or parameter, under the same scene, (1) the preset face recognition image program is larger than an aperture opening of the license plate recognition image program for the aperture opening size, (2) the preset face recognition image program is longer than a fast time of the license plate recognition image program for the fast time, (3) the preset face recognition image program is higher than the gain of the license plate recognition image program for the gain size, and (4) the preset face recognition image program is higher than the fill-in light intensity of the license plate recognition image program for the fill-in light intensity.
Step S203: and calling a preset general image program to identify the outlines of the people and the vehicles in the camera image.
In step S203, a preset general-purpose image program is used to cause the phenomena of license plate overexposure and face blackness, so that the license plate and the face cannot be recognized at the same time, but the outlines of the person and the vehicle in the camera image can be recognized.
Step S204: it is determined whether a person and a vehicle are simultaneously present in the camera image.
Step S204 in the present embodiment is similar to step S102 in fig. 1, and executes step S205 and step S206 when a person and a vehicle are present in the camera image at the same time, executes step S207 when only a person is present in the camera image, executes step S208 when only a vehicle is present in the camera image, and executes step S209 when a person and a vehicle are not present in the camera image.
Step S205: the speed of the person and the vehicle is detected.
Step S205 in the present embodiment is similar to step S103 in fig. 1.
Step S206: it is determined whether the speed of the person is greater than the speed of the vehicle.
In the present embodiment, step S206 is executed after step S205, and when the speed of the person is greater than the speed of the vehicle, step S2061 is executed: the method comprises the steps of calling a preset face recognition image program, then calling a preset license plate recognition image program, saving a face recognition result after calling the preset face recognition image program, saving a camera image containing the face recognition result, and saving the face recognition result extracted from the camera image; the method also comprises the step of storing the license plate recognition result after calling the preset license plate recognition image program, and can store a camera image containing the license plate recognition result and also can store the license plate recognition result extracted from the camera image. After step S2061, step S203 is cyclically executed.
When the speed of the vehicle is higher than the speed of a person, the step S2062 is executed to call a preset license plate recognition image program, then call a preset face recognition image program, and save license plate recognition results after calling the preset license plate recognition image program, wherein the camera image containing the license plate recognition results can be saved, and the license plate recognition results extracted from the camera image can also be saved; the method also comprises the step of saving the face recognition result after the preset face recognition image program is called, and can save a camera image containing the face recognition result and also can save the face recognition result extracted from the camera image. After step S2062, step S203 is executed cyclically.
When the speed of a person is equal to that of a vehicle, a preset license plate recognition image program is called preferentially, and then a preset face recognition image program is called. In this embodiment, when the speed of the person outside the vehicle is equal to the speed of the vehicle, the preset license plate recognition image program is called first, and then the preset face recognition image program is called, and the person inside the vehicle and the vehicle are also suitable for calling the preset license plate recognition image program first, and then the preset face recognition image program is called.
Step S207: and calling a preset face recognition image program.
In step S207, the step of calling the preset face recognition image program further includes saving a face recognition result, which may be saving a camera image containing the face recognition result, or saving a face recognition result extracted from the camera image. After step S207, step S203 is executed cyclically.
Step S208: and calling a preset license plate recognition image program.
In step S208, the step of saving the license plate recognition result after calling the preset license plate recognition image program may be performed, and the camera image including the license plate recognition result may be saved, or the license plate recognition result extracted from the camera image may be saved. After step S208, step S203 is executed cyclically.
Step S209: and calling a preset general image program.
After step S209, step S203 is executed cyclically.
The camera image processing method according to the second embodiment of the present invention calls different image programs according to the detection result on the basis of the th embodiment to accurately identify the face and the license plate in the image, thereby not only ensuring the identification function of the identification camera and improving the identification efficiency, but also considering the identification effects of multiple scenes and objects to be identified with different reflectivities.
Fig. 3 is a schematic structural diagram of a camera image processing apparatus according to an embodiment of the present invention, as shown in fig. 3, the apparatus 30 includes an image acquisition module 31, a determination module 32, a detection module 33, a judgment module 34, and an execution module 35.
The image acquisition module 31 is used for acquiring camera images.
In this embodiment, the camera image may be a video image or a single frame image.
The determination module 32 is coupled to the image acquisition module 31 for determining whether a person and a vehicle are present in the camera image at the same time.
In this embodiment, the determination module 32 includes an acquisition unit for acquiring picture data in the camera image and a determination unit coupled to the acquisition unit for determining whether a person and a vehicle are simultaneously present in the camera image based on the picture data, the picture data in the camera image includes contour data of the person and contour data of the vehicle, the determination unit may have two preferred embodiments, in the embodiment, determining whether the person and the vehicle are simultaneously present in the camera image based on the picture data and a preset contour, the preset contour includes a preset vehicle type and a preset human type, comparing the picture data with the preset vehicle type, detecting the presence of the vehicle in the camera image when a contour corresponding to a preset vehicle type is present in the picture data, comparing the picture data with the preset human type, detecting the presence of the person and the vehicle in the camera image when a contour corresponding to the preset human type is present in the picture data, in the embodiment, determining whether the person and the vehicle are simultaneously present in the camera image based on the acquired picture data using a depth learning algorithm, creating a recognition model, each of the sets of data including the training data including the person and/or the vehicle image, outputting the result of the presence of the detected person and the vehicle in the camera image, outputting the camera image as the result of the human and outputting the camera image when the human and the camera image are the human and outputting the result of the vehicle.
The detection module 33 is coupled to the determination module 32 for detecting the speed of the person and the vehicle when both are present in the camera image.
In this embodiment, the detection module 33 obtains multiple camera images, where people and vehicles are present in the camera images; selecting two frames of camera images, recording the shooting time of the two frames of camera images, and respectively calculating the displacement of a person and the displacement of a vehicle; the speed of the person and the speed of the vehicle are calculated from the photographing time, the displacement amount of the person, and the displacement amount of the vehicle, respectively. The speed of the person is the ratio of the displacement of the person to the shooting time difference of the two frames of camera images, and the speed of the vehicle is the ratio of the displacement of the vehicle to the shooting time difference of the two frames of camera images.
The decision module 34 is coupled to the detection module 33 for determining the faster and slower of the speed of the person and the speed of the vehicle.
In the present embodiment, the faster the speed is, the earlier the person and the vehicle come from the camera appears within the shooting range of the camera.
The executing module 35 is coupled to the determining module 34, and configured to, according to the determination result of the determining module 34, first call the identification image program corresponding to the faster to perform image identification, and then call the identification image program corresponding to the slower to perform image identification.
The execution module 35 calls an image recognition program corresponding to a person to perform face recognition, and an image recognition program corresponding to a vehicle to perform license plate recognition. And comparing the speed of the person with the speed of the vehicle, and calling the identification image program corresponding to the person and then calling the identification image program corresponding to the vehicle when the speed of the person is greater than the speed of the vehicle. When the speed of the vehicle is higher than that of the person, the identification image program corresponding to the vehicle is called first, and then the identification image program corresponding to the person is called. When the speed of the person is equal to that of the vehicle, the identification image program corresponding to the vehicle is called preferentially, and then the identification image program corresponding to the person is called. In this embodiment, when the speed of the person outside the vehicle is equal to the speed of the vehicle, the identification image program corresponding to the vehicle is called with priority, and the identification image program corresponding to the person is called again.
Fig. 4 is a schematic structural diagram of a camera image processing apparatus according to a second embodiment of the present invention, as shown in fig. 4, the apparatus 40 includes an image acquisition module 41, an image program presetting module 42, an th calling module 43, a determination module 44, a detection module 45, a judgment module 46, a th control module 461, a second control module 462, a second calling module 47, a third calling module 48, and a fourth calling module 49.
The image acquisition module 41 is used for acquiring camera images.
In this embodiment, the camera image may be a video image or a single frame image.
The image program presetting module 42 and the image acquiring module 41 are configured to preset image programs, where the image programs include a license plate recognition image program, a face recognition image program, and a general image program.
In this embodiment, the image program presetting module 42 adjusts the camera data according to the reflection characteristics of the human face or the human body, and the camera data adjusted to be capable of recognizing the human face information is a preset human face recognition image program; adjusting camera data according to the reflection characteristic of the license plate, wherein the camera data when the license plate information can be identified is a preset license plate identification image program; and adjusting the camera data according to the environment, wherein the camera data when the camera data is adjusted to be capable of identifying the outlines of the people and the vehicle is a preset general image program.
The preset face recognition image program, the preset license plate recognition image program and the preset general image program all comprise an aperture control mode or parameter, a fast control mode or parameter, a gain control mode or parameter and a fill-in light intensity control mode or parameter, under the same scene, (1) the preset face recognition image program is larger than the aperture opening of the license plate recognition image program for the aperture opening size, (2) the preset face recognition image program is longer than the fast time of the license plate recognition image program for the fast time, (3) the preset face recognition image program is higher than the gain of the license plate recognition image program for the gain size, and (4) the preset face recognition image program is higher than the fill-in light intensity of the license plate recognition image program for the fill-in light intensity, so that in the actual working process, the preset face recognition image program and the license plate recognition image program can simultaneously meet at least conditions in the steps (1), (2), (3) and (4).
The th calling module 43 is coupled to the image program presetting module 42 for calling the preset general image program to recognize the outlines of the person and the vehicle in the camera image.
In this embodiment, the phenomenon of license plate overexposure and face overexposure exists by adopting a preset general image program, so that the license plate and the face cannot be recognized at the same time, but the outlines of a person and a vehicle in the image of the camera can be recognized.
The determination module 44 is coupled to the th call module 43 for determining whether a person and a vehicle are both present in the camera image.
The determination module 44 of this embodiment is similar to the determination module 32 in fig. 3, and is not described herein again.
The detection module 45 is coupled to the determination module 44 for detecting the speed of the person and the vehicle when both are present in the camera image.
The determination module 46 is coupled to the detection module 45 for determining whether the speed of the person is greater than the speed of the vehicle.
The th control module 461 is coupled to the determining module 46 and the image program presetting module 42, respectively, and when the determination result is that the speed of the person is greater than the speed of the vehicle, the th control module 461 invokes the preset face recognition image program and then invokes the preset license plate recognition image program.
The second control module 462 is coupled to the determining module 46 and the image program presetting module 42, respectively, and when the determination result is that the speed of the vehicle is greater than the speed of the person, the second control module 462 invokes a preset license plate recognition image program and then invokes a preset face recognition image program.
The second calling module 47 is respectively coupled to the determining module 44 and the image program presetting module 42, and is used for calling the preset face recognition image program by the second calling module 47 when only a person exists in the camera image.
The third calling module 48 is coupled to the determining module 44 and the image program presetting module 42, respectively, and is configured to, when only a vehicle exists in the camera image, call the preset license plate recognition image program by the third calling module 48.
The fourth calling module 49 is coupled to the determining module 44 and the image program presetting module 42, respectively, and is used for calling the preset general image program by the fourth calling module 49 when no person or vehicle exists in the camera image.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a codec according to an embodiment of the invention. As shown in fig. 5, the codec 50 includes a processor 51 and a memory 52 coupled to the processor 51.
The memory 52 stores program instructions for implementing the camera image processing method of any of the embodiments described above.
The processor 51 is operative to execute program instructions stored in the memory 52 to process the camera images.
The processor 51 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable array (FPGA) or other programmable logic device, a discrete or transistor logic device, a discrete hardware component, or the like.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a storage apparatus according to an embodiment of the present invention, where the storage apparatus according to an embodiment of the present invention stores a program file 61 capable of implementing all the methods described above, where the program file 61 may be stored in the storage apparatus in the form of a software product, and includes several instructions to enable computer devices (which may be personal computers, servers, or network devices) or processors (processors) to execute all or part of the steps of the methods described in the embodiments of the present application.
For example, the above-described embodiments of the apparatus are merely illustrative, e.g., the division of units into logical functional divisions, and other divisions may be possible in actual practice, e.g., multiple units or components may be combined or integrated into another systems, or features may be omitted or not implemented.at , the shown or discussed coupling or direct coupling or communication connection between each other may be through interfaces, and the indirect coupling or communication connection of the apparatuses or units may be electrical, mechanical or other forms.
In addition, the functional units in the embodiments of the present invention may be integrated into processing units, or each unit may exist alone physically, or two or more units are integrated into units.
The above embodiments are merely examples and are not intended to limit the scope of the present disclosure, and all modifications, equivalents, and flow charts using the contents of the specification and drawings of the present disclosure or those directly or indirectly applied to other related technical fields are intended to be included in the scope of the present disclosure.
Claims (10)
1, camera image processing method, comprising:
acquiring a camera image;
determining whether a person and a vehicle are present in the camera image at the same time;
detecting the speed of the person and the vehicle when the person and the vehicle exist in the camera image at the same time;
determining the faster and slower of the speed of the person and the speed of the vehicle;
and calling the identification image program corresponding to the faster person to perform image identification, and calling the identification image program corresponding to the slower person to perform image identification.
2. The camera image processing method according to claim 1,
the step of determining whether a person and a vehicle are present in the camera image at the same time includes:
acquiring picture data in the camera image;
and determining whether a person and a vehicle exist in the camera image at the same time according to the picture data.
3. The camera image processing method according to claim 2, wherein the determining whether a person and a vehicle are present in the camera image at the same time comprises:
presetting an image program, wherein the image program comprises a license plate recognition image program, a face recognition image program and a general image program;
and calling the preset general image program to identify the outlines of people and vehicles in the camera image.
4. A camera image processing method according to claim 3, characterized in that the step of presetting the image program comprises:
adjusting camera data according to the reflection characteristics of the human face or the human body, wherein the camera data when the human face information can be recognized is a preset human face recognition image program;
adjusting camera data according to the reflection characteristic of the license plate, wherein the camera data when the license plate information can be identified is a preset license plate identification image program;
adjusting camera data according to the environment, wherein the camera data when the camera data can be adjusted to identify the outlines of people and vehicles is a preset general image program;
the preset face recognition image program, the preset license plate recognition image program and the preset general image program respectively comprise an aperture control mode or parameter, a fast control mode or parameter, a gain control mode or parameter and a fill-in light intensity control mode or parameter.
5. The camera image processing method according to claim 3,
determining the faster and the slower of the speed of the person and the speed of the vehicle, calling the identification image program corresponding to the faster to perform image identification, and then calling the identification image program corresponding to the slower to perform image identification comprises:
judging whether the speed of the person is greater than the speed of the vehicle;
when the speed of the person is greater than the speed of the vehicle, calling the preset face recognition image program, and then calling the preset license plate recognition image program;
and when the speed of the vehicle is higher than the speed of the person, calling the preset license plate recognition image program, and then calling the preset face recognition image program.
6. The camera image processing method according to claim 3, wherein said determining whether a person and a vehicle are simultaneously present in the camera image comprises:
when only a person exists in the camera image, calling the preset face recognition image program;
when only a vehicle exists in the camera image, calling the preset license plate recognition image program;
and when no person or vehicle exists in the camera image, calling the preset general image program.
7. The camera image processing method according to claim 5 or 6,
after the preset face recognition image program is called, a face recognition result is stored;
and after the preset license plate recognition image program is called, storing a license plate recognition result.
8. The camera image processing method according to claim 1, wherein the step of detecting the speeds of the person and the vehicle when the person and the vehicle are simultaneously present in the camera image comprises:
acquiring multiple frames of camera images, wherein the people and the vehicle exist in the camera images;
selecting two frames of the camera images, recording shooting time of the two frames of the camera images, and respectively calculating the displacement of the person and the displacement of the vehicle;
and respectively calculating the speed of the person and the speed of the vehicle according to the shooting time, the displacement of the person and the displacement of the vehicle.
A codec of the type 9, , comprising a processor, a memory coupled to the processor, wherein,
the memory stores program instructions for implementing the camera image processing method of any of claims 1-8;
the processor is to execute the program instructions stored by the memory to process a camera image.
storage device, characterized in that a program file capable of realizing the camera image processing method according to any of claims 1-8 is stored.
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| CN104253949A (en) * | 2013-06-27 | 2014-12-31 | 安讯士有限公司 | Method and apparatus for setting a camera exposure time |
| CN103559498A (en) * | 2013-09-24 | 2014-02-05 | 北京环境特性研究所 | Rapid man and vehicle target classification method based on multi-feature fusion |
| CN104144325A (en) * | 2014-07-08 | 2014-11-12 | 北京汉王智通科技有限公司 | Monitoring method and monitoring device |
| CN104282150A (en) * | 2014-09-29 | 2015-01-14 | 北京汉王智通科技有限公司 | Recognition device and system of moving target |
| US20160314353A1 (en) * | 2015-04-21 | 2016-10-27 | Placemeter Inc. | Virtual turnstile system and method |
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