CN106899829A - A kind of method for processing video frequency and device - Google Patents

Abstract

The embodiment of the present invention provides a video processing method and device, the method comprising: receiving the face image of the control object sent by the terminal; acquiring a video file within the target control range; determining from the video file the N video images matched with the face images; and determine the activity place of the controlled object according to the N video images. Through the embodiment of the present invention, the activity place of the controlled object can be quickly discovered, and further, it is convenient for the user to analyze the activity rule of the controlled object.

Description

A video processing method and device

technical field

The invention relates to the technical field of video surveillance, in particular to a video processing method and device.

Background technique

With the rapid development of economy, society, and culture, the influence at home and abroad is increasing day by day, and more and more migrants are moving to cities. While the increase in population is accelerating the process of urbanization, it also brings greater challenges to urban management. Although , video surveillance provides technical support for urban security. However, at present, cameras have been laid out in cities, and the functions of each camera are relatively independent. When it is necessary to search for a target person, it is often done manually. The video images captured by the camera are viewed frame by frame. Therefore, it is impossible to quickly find the control object, and furthermore, it is impossible to quickly determine the activity place of the control object, and it is impossible to find the activity law of the control object.

Contents of the invention

The embodiment of the present invention provides a video processing method and device, which can quickly find the activity place of the control object.

The first aspect of the embodiment of the present invention provides a video processing method, including:

Receive the face image of the controlled object sent by the terminal;

Obtain video files within the control range of the target;

Determining N video images matching the face images from the video file;

An activity location of the controlled object is determined according to the N video images.

With reference to the first aspect of the embodiments of the present invention, in the first possible implementation manner of the first aspect, the acquisition of video files within the control range of the target includes:

Obtain the control time period selected by the user;

Selecting the video files within the control time period and the target control range from the historical video library.

With reference to the first aspect of the embodiments of the present invention or the first possible implementation manner of the first aspect, in the second possible implementation manner of the first aspect, the determination from the video file that matches the face image The N video images, including:

The video file is analyzed to obtain Q video images, and the Q is a positive integer;

Eliminate video images that do not contain human face images in the Q video images to obtain P video images, and the P is an integer less than or equal to the Q;

Matching the face images with the P video images respectively to obtain the P matching values;

Selecting the N matching values greater than the first preset threshold among the P matching values, and acquiring their corresponding video images.

With reference to the first aspect or the first possible implementation manner of the first aspect of the embodiments of the present invention, in the third possible implementation manner of the first aspect, each of the N video images corresponds to a position marker;

The determining the activity place of the controlled object according to the N video images includes:

Divide the N video images into M categories according to the position marks, and the M is an integer less than or equal to the N;

Select a category whose number of video images in the M category is greater than a second preset threshold to obtain a K category, and use the position mark corresponding to the K category as the activity place of the controlled object.

With reference to the first aspect of the embodiments of the present invention or the first possible implementation manner of the first aspect, in the fourth possible implementation manner of the first aspect, in determining the activity of the controlled object according to the N video images After the site, the method also includes:

Pushing the event location to the terminal.

The second aspect of the embodiment of the present invention provides a video processing device, including:

a receiving unit, configured to receive the face image of the controlled object sent by the terminal;

an acquisition unit, configured to acquire video files within the range of target deployment;

A first determining unit, configured to determine N video images matching the human face image from the video file;

The second determining unit is configured to determine an activity location of the controlled object according to the N video images.

With reference to the second aspect of the embodiments of the present invention, in a first possible implementation manner of the second aspect, the acquiring unit includes:

An acquisition module, configured to acquire the control time period selected by the user;

The first selection module is used to select video files within the control time period and the target control range from the historical video library.

With reference to the second aspect of the embodiment of the present invention or the first possible implementation manner of the second aspect, in the second possible implementation manner of the second aspect, the first determination unit includes:

An analysis module, configured to analyze the video file to obtain Q video images, where the Q is a positive integer;

The elimination module is used to eliminate video images that do not contain human face images in the Q video images to obtain P video images, and the P is an integer less than or equal to the Q;

A matching module, configured to match the face images with the P video images respectively to obtain the P matching values;

The second selecting module is configured to select the N matching values greater than the first preset threshold among the P matching values, and acquire their corresponding video images.

With reference to the second aspect of the embodiment of the present invention or the first possible implementation manner of the second aspect, in the third possible implementation manner of the second aspect, each of the N video images corresponds to a position marker;

The second determination unit includes:

A division module, configured to divide the N video images into M categories according to position marks, and the M is an integer less than or equal to the N;

The third selection module is configured to select a category whose video image quantity is greater than a second preset threshold in the M category, obtain a K category, and use the position mark corresponding to the K category as the activity place of the controlled object.

With reference to the second aspect or the first possible implementation manner of the second aspect of the embodiments of the present invention, in the fourth possible implementation manner of the second aspect, the video processing device further includes:

A pushing unit, configured to push the activity location of the controlled object to the terminal after the second determining unit determines the activity location of the controlled object according to the N video images.

Implementing the embodiment of the present invention has the following beneficial effects:

It can be seen that, through the embodiment of the present invention, the face image of the control object sent by the terminal is received, and the video file within the target control range is obtained;

Determining N video images matching the face images from the video file;

An activity location of the controlled object is determined according to the N video images.

It can be seen that through the embodiment of the present invention, the face image of the control object sent by the terminal is received, the video file within the target control range is obtained, and N video images matching the face image are determined from the video file. According to the N A video image is used to determine the activity place of the controlled object. Therefore, the activity place of the controlled object can be determined, and further, it is convenient for the user to analyze the activity rule of the controlled object.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings that need to be used in the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without making creative efforts.

FIG. 1 is a schematic flowchart of a first embodiment of a video processing method provided by an embodiment of the present invention;

FIG. 2 is a schematic flowchart of a second embodiment of a video processing method provided by an embodiment of the present invention;

Fig. 3a is a schematic structural diagram of a first embodiment of a video processing device provided by an embodiment of the present invention;

Fig. 3b is a schematic structural diagram of an acquisition unit of the video processing device described in Fig. 3a provided by an embodiment of the present invention;

Fig. 3c is a schematic structural diagram of a first determination unit of the video processing device described in Fig. 3a provided by an embodiment of the present invention;

Fig. 3d is a schematic structural diagram of a second determining unit of the video processing device described in Fig. 3a provided by an embodiment of the present invention;

Fig. 3e is another schematic structural diagram of the video processing device described in Fig. 3a provided by an embodiment of the present invention;

Fig. 4 is a schematic structural diagram of a second embodiment of a video processing device provided by an embodiment of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

The terms "first", "second", "third" and "fourth" in the description and claims of the present invention and the drawings are used to distinguish different objects, rather than to describe a specific order . Furthermore, the terms "include" and "have", as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or units inherent in these processes, methods, products or apparatuses.

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 one embodiment of the present invention. The presentation of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are independent or alternative embodiments mutually exclusive of other embodiments. It is understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments.

The video processing device described in this embodiment of the present invention may be a server or a cloud platform.

It should be noted that the video processing device in the embodiment of the present invention can be connected with multiple cameras, and each camera can be used to capture video images, and each camera can have a corresponding position mark, or there can be a corresponding number. Usually, cameras can be set up in public places, such as schools, museums, intersections, pedestrian streets, office buildings, garages, airports, hospitals, subway stations, stations, bus stops, supermarkets, hotels, entertainment venues, etc. After the video image is captured by the camera, the video image can be saved to the memory of the system where the video processing device is located. Multiple image libraries can be stored in the memory, and each image library can contain different video images of the same person. Of course, each image library can also be used to store video images of an area or video images captured by a specified camera.

Further optionally, in the embodiment of the present invention, each frame of video image captured by the camera corresponds to an attribute information, and the attribute information is at least one of the following: the shooting time of the video image, the location of the video image, and the attribute parameter of the video image ( format, size, resolution, etc.), the number of the video image, and the attributes of the characters in the video image. The characteristic attributes of the characters in the video image may include, but not limited to: the number of characters in the video image, the position of the characters, the angle of the characters, and the like.

It should be further noted that the video image collected by each camera is usually a dynamic face image, therefore, in the embodiment of the present invention, the angle information of the face image can be planned, and the above angle information can include but not limited to: horizontal rotation angle , pitch angle or inclination. For example, it can be defined that the dynamic face image data requires that the distance between the two eyes is not less than 30 pixels, and it is recommended to be more than 60 pixels. The horizontal rotation angle does not exceed ±30°, the pitch angle does not exceed ±20°, and the tilt angle does not exceed ±45°. It is recommended that the horizontal rotation angle not exceed ±15°, the pitch angle not exceed ±10°, and the tilt angle not exceed ±15°. For example, it can also filter whether the face image is blocked by other objects. Normally, accessories should not cover the main area of the face, such as dark sunglasses, masks and exaggerated jewelry. Of course, the camera may be covered with dust , causing the face image to be occluded. The picture format of the video image in the embodiment of the present invention can include but not limited to: BMP, JPEG, JPEG2000, PNG etc., its size can be between 10-30KB, each video image can also correspond to a shooting time, and shooting Information such as the uniform number of the camera of the video image, the link to the large panorama image corresponding to the face image (the feature correspondence relationship file is established between the face image and the global image).

It should be noted that, in the embodiment of the present invention, the activity place of the control object is mainly determined by the activity place where the camera is located, and the activity place of the control object may include but not limited to: schools, hospitals, museums, buses, subway stations, high-speed rail Stations, stations, streets, stadiums, scenic spots, etc. There may be one or more activity places of the controlled object, and of course, different activity places of the controlled object are located at different times.

Please refer to FIG. 1 , which is a schematic flowchart of a first embodiment of a video processing method provided by an embodiment of the present invention. The video processing method described in this embodiment includes the following steps:

101. Receive the face image of the controlled object sent by the terminal.

Wherein, the terminal can establish a network connection with the video processing device, and the terminal can send a face image of a controlled object to the video processing device. In practical applications, the video processing device can also load the face image by itself. After the administrator of the video processing device passes the identity verification, he can load at least one face image of the controlled object. In this way, the setting of the controlled object can be realized. .

Optionally, between step 101 and step 102, the following steps may also be included:

The video processing device can match the face image in step 101 with the face image in the controlled object database, and execute step 102 after the matching is successful.

102. Obtain the video files within the control range of the target.

Wherein, the target deployment range may be specified by the user, or may be defaulted to a specific range (for example, within the monitoring range of all cameras). The video processing device can obtain video files within the target deployment range from the historical video library.

Optionally, in the above-mentioned step 102, obtaining the video files within the target deployment range may include the following steps:

21) Obtain the control time period selected by the user;

22). Selecting the video files within the control time period and the target control range from the historical video library.

Wherein, the above-mentioned historical video library may include video files captured by all cameras within the monitoring range. Usually, the longer the monitoring time of the video is, the larger its memory is. Therefore, the control time period selected by the user can be obtained. For different cameras, the control time period of each camera can be different. Of course, all cameras The deployment and control time period can also be the same, specifically, it depends on the actual situation. The above-mentioned target deployment range can be part of the monitoring range, that is, the target deployment range can be formed by the monitoring area of one or more cameras specified by the user, or the target deployment range can be formed by cameras within a certain area specified by the user. Taking a camera within the control range of the target as an example, the camera can continue to shoot, so it can record video at different times, and what the user needs is the video file within the control time period, so the corresponding history of the camera can be The video file corresponding to the cut-off deployment time period in the video file.

Wherein, in step 21, the user may input the deployment control time period, of course, the deployment control time period for each camera within the target deployment control range may be unified. Alternatively, each camera within the target monitoring range corresponds to a different monitoring time period, because the probability of the monitoring object appearing in the monitoring range of different cameras at the same time is relatively small, therefore, more often the monitoring object will only be in one at a time. within the monitoring range of the camera. Therefore, different cameras can correspond to different control time periods. Further, the video processing device may select video files within the control time period and target control range from the historical video library. Certainly, when there are multiple cameras within the control range of the target, each camera may correspond to a video file, and all video files may be regarded as or synthesized into one video file.

103. Determine N video images that match the face image from the video file.

Wherein, multiple video images may be included in the video file, and each video image may be matched with a human face image, therefore, each video image in the multiple video images may be matched with a human face image, thereby obtaining the N video images for face image matching, where N is a positive integer.

Optionally, in the above-mentioned step 103, determining N video images matching the human face images from the video file may include the following steps:

31), the video file is analyzed to obtain Q video images, and the Q is a positive integer;

32), remove the video images that do not contain human face images in the Q video images, and obtain P video images, and the P is an integer less than or equal to the Q;

33), matching the face images with the P pieces of video images respectively, to obtain the P matching values;

34). Selecting the N matching values greater than the first preset threshold among the P matching values, and acquiring their corresponding video images.

Wherein, the above-mentioned first preset threshold may be defaulted by the system or set by the user. Usually, the video file is a complete file, therefore, the video file needs to be parsed to obtain video images one by one. In step 31, the video file may be parsed to obtain Q video images, where Q is a positive integer. Of course, not every one of the Q video images contains a human face image, therefore, the video images that do not contain a human face image in the Q video images can be eliminated to obtain P video images, therefore, P can be selected Among the matching values, N matching values greater than the first preset threshold are obtained, and video images corresponding to the N matching values are acquired to obtain N video images.

104. Determine an activity location of the controlled object according to the N video images.

Optionally, each video image in the N video images corresponds to a position marker; in the above step 104, determining the activity site of the controlled object according to the N video images may include the following steps:

41), dividing the N video images into M categories according to the position mark, and the M is an integer less than or equal to the N;

42). Select the category whose number of video images in the M category is greater than the second preset threshold to obtain the K category, and use the position mark corresponding to the K category as the activity place of the controlled object.

Wherein, each video image is captured by a camera, therefore, each video image corresponds to a position mark, and the position marks are the same in different activity places. Of course, in the same activity place, the same position mark can be selected, Of course, different location markers can be selected in the same activity place. For example, if there is only one camera in a certain activity place, the activity place where the camera is located can be used as the location marker or the number of the camera can be used as the location marker. For another example, if there are multiple cameras in a certain activity place, and each camera has a camera number, such as: 0060-0089, then the camera with the position mark at 0060-0089 can be regarded as an activity place. The above-mentioned second preset threshold can be set by default by the system or by the user.

Optionally, the video processing device can divide the N video images into M categories according to the position marks, of course, each category contains at least one video image, M is an integer less than or equal to N, and the video images in the M categories can be selected The category whose quantity is greater than the second preset threshold value is obtained, and the K category is obtained, and the position mark corresponding to the K category is used as the activity place of the controlled object. Of course, K is an integer greater than or equal to 1. Therefore, when K is 1, one activity place is obtained, and when K is greater than 1, two or more activity places are obtained.

It can be seen that through the embodiment of the present invention, the face image of the control object sent by the terminal is received, the video file within the target control range is obtained, and N video images matching the face image are determined from the video file. According to the N A video image is used to determine the activity place of the controlled object. Therefore, the activity place of the controlled object can be determined, and further, it is convenient for the user to analyze the activity rule of the controlled object.

Consistent with the above, please refer to FIG. 2 , which is a schematic flowchart of a second embodiment of a video processing method provided by an embodiment of the present invention. The video processing method described in this embodiment includes the following steps:

201. Receive a face image of a controlled object sent by a terminal.

Wherein, the terminal can establish a network connection with the video processing device, and the terminal can send a face image of a controlled object to the video processing device. In practical applications, the video processing device can also load the face image by itself. After the administrator of the video processing device passes the identity verification, he can load at least one face image of the controlled object. In this way, the setting of the controlled object can be realized. .

Optionally, between step 201 and step 202, the following steps may also be included:

The video processing device can match the face image in step 201 with the face image in the controlled object library, and then execute step 202 after the matching is successful.

202. Acquire the video files within the control range of the target.

Wherein, the target deployment range may be specified by the user, or may be defaulted to a specific range (for example, within the monitoring range of all cameras). The video processing device can obtain video files within the target deployment range from the historical video library.

Optionally, in the above-mentioned step 202, obtaining the video files within the control range of the target may include the following steps:

21) Obtain the control time period selected by the user;

22). Selecting the video files within the control time period and the target control range from the historical video library.

Wherein, the above-mentioned historical video library may include video files captured by all cameras within the monitoring range. Usually, the longer the monitoring time of the video is, the larger its memory is. Therefore, the control time period selected by the user can be obtained. For different cameras, the control time period of each camera can be different. Of course, all cameras The deployment and control time period can also be the same, specifically, it depends on the actual situation. The above-mentioned target deployment range can be part of the monitoring range, that is, the target deployment range can be formed by the monitoring area of one or more cameras specified by the user, or the target deployment range can be formed by cameras within a certain area specified by the user. Taking a camera within the control range of the target as an example, the camera can continue to shoot, so it can record video at different times, and what the user needs is the video file within the control time period, so the corresponding history of the camera can be The video file corresponding to the cut-off deployment time period in the video file.

Wherein, in step 21, the user may input the deployment control time period, of course, the deployment control time period for each camera within the target deployment control range may be unified. Alternatively, each camera within the target monitoring range corresponds to a different monitoring time period, because the probability of the monitoring object appearing in the monitoring range of different cameras at the same time is relatively small, therefore, more often the monitoring object will only be in one at a time. within the monitoring range of the camera. Therefore, different cameras can correspond to different control time periods. Further, the video processing device may select video files within the control time period and target control range from the historical video library. Certainly, when there are multiple cameras within the control range of the target, each camera may correspond to a video file, and all video files may be regarded as or synthesized into one video file.

203. Determine N video images that match the face image from the video file.

Wherein, multiple video images may be included in the video file, and each video image may be matched with a human face image, therefore, each video image in the multiple video images may be matched with a human face image, thereby obtaining the N video images for face image matching, where N is a positive integer.

Optionally, in the above-mentioned step 203, determining N video images matching the human face images from the video file may include the following steps:

31), the video file is analyzed to obtain Q video images, and the Q is a positive integer;

32), remove the video images that do not contain human face images in the Q video images, and obtain P video images, and the P is an integer less than or equal to the Q;

33), matching the face images with the P pieces of video images respectively, to obtain the P matching values;

34). Selecting the N matching values greater than the first preset threshold among the P matching values, and acquiring their corresponding video images.

Wherein, the above-mentioned first preset threshold may be defaulted by the system or set by the user. Usually, the video file is a complete file, therefore, the video file needs to be parsed to obtain video images one by one. In step 31, the video file may be parsed to obtain Q video images, where Q is a positive integer. Of course, not every one of the Q video images contains a human face image, therefore, the video images that do not contain a human face image in the Q video images can be eliminated to obtain P video images, therefore, P can be selected Among the matching values, N matching values greater than the first preset threshold are obtained, and video images corresponding to the N matching values are acquired to obtain N video images.

204. Determine an activity location of the controlled object according to the N video images.

Optionally, each video image in the N video images corresponds to a position marker; in the above step 204, determining the activity site of the controlled object according to the N video images may include the following steps:

41), dividing the N video images into M categories according to the position mark, and the M is an integer less than or equal to the N;

42). Select the category whose number of video images in the M category is greater than the second preset threshold to obtain the K category, and use the position mark corresponding to the K category as the activity place of the controlled object.

Wherein, each video image is captured by a camera, therefore, each video image corresponds to a position mark, and the position marks are the same in different activity places. Of course, in the same activity place, the same position mark can be selected, Of course, different location markers can be selected in the same activity place. For example, if there is only one camera in a certain activity place, the activity place where the camera is located can be used as the location marker or the number of the camera can be used as the location marker. For another example, if there are multiple cameras in a certain activity place, and each camera has a camera number, such as: 0060-0089, then the camera with the position mark at 0060-0089 can be regarded as an activity place. The above-mentioned second preset threshold can be set by default by the system or by the user.

Optionally, the video processing device can divide the N video images into M categories according to the position marks, of course, each category contains at least one video image, M is an integer less than or equal to N, and the video images in the M categories can be selected The category whose quantity is greater than the second preset threshold value is obtained, and the K category is obtained, and the position mark corresponding to the K category is used as the activity place of the controlled object. Of course, K is an integer greater than or equal to 1. Therefore, when K is 1, one activity place is obtained, and when K is greater than 1, two or more activity places are obtained.

205. Push the event location to the terminal.

Wherein, in step 204, after the activity place of the controlled object is determined, the activity place may be pushed to the terminal. The terminal can keep abreast of the frequent entry and exit places of the controlled objects.

It can be seen that through the embodiment of the present invention, the face image of the control object sent by the terminal is received, the video file within the target control range is obtained, and N video images matching the face image are determined from the video file. According to the N A video image determines the activity place of the controlled object, and pushes the activity place to the terminal. Therefore, the activity place of the controlled object can be determined. In addition, the end user can know in time the activity places where the controlled object frequently enters and exits, and furthermore, it is convenient for the user to analyze the activity law of the controlled object.

Consistent with the above, the following is the device for implementing the above video processing method, specifically as follows:

Please refer to FIG. 3 a , which is a schematic structural diagram of a first embodiment of a video processing device provided by an embodiment of the present invention. The video processing device described in this embodiment includes: a receiving unit 301, an acquiring unit 302, a first determining unit 303 and a second determining unit 304, specifically as follows:

The receiving unit 301 is configured to receive the face image of the controlled object sent by the terminal;

An acquisition unit 302, configured to acquire video files within the target deployment range;

The first determining unit 303 is configured to determine N video images matching the human face image from the video file;

The second determining unit 304 is configured to determine an activity location of the controlled object according to the N video images.

Optionally, as shown in FIG. 3b, FIG. 3b is a specific detailed structure of the acquisition unit 302 in the video processing device described in FIG. 3a. The acquisition unit 302 may include: an acquisition module 3021 and a first selection module 3022, specifically as follows:

Obtaining module 3021, configured to obtain the deployment time period selected by the user;

The first selection module 3022 is configured to select video files within the control time period and the target control range from the historical video library.

Optionally, as shown in FIG. 3c, FIG. 3c is a specific detailed structure of the first determination unit 303 in the video processing device described in FIG. , matching module 3033 and the second selection module 3034, specifically as follows:

The parsing module 3031 is configured to parse the video file to obtain Q video images, where the Q is a positive integer;

The elimination module 3032 is used to eliminate video images that do not contain human face images in the Q video images to obtain P video images, and the P is an integer less than or equal to the Q;

A matching module 3033, configured to match the face images with the P video images respectively to obtain the P matching values;

The second selection module 3034 is configured to select the N matching values greater than the first preset threshold among the P matching values, and acquire their corresponding video images.

Optionally, as shown in FIG. 3d, FIG. 3d is a specific detailed structure of the second determining unit 304 in the video processing device described in FIG. 3a, each of the N video images corresponds to a position marker; The second determination unit 304 may include: a division module 3041 and a third selection module 3042, specifically as follows:

A division module 3041, configured to divide the N video images into M categories according to position marks, where M is an integer less than or equal to N;

The third selection module 3042 is configured to select a category whose number of video images in the M category is greater than a second preset threshold, obtain a K category, and use the position mark corresponding to the K category as the activity place of the controlled object.

Optionally, as shown in FIG. 3e, FIG. 3e is another modified structure of the video processing device described in FIG. 3a. Compared with FIG. 3a, FIG. 3e may also include: a push unit 305, specifically as follows:

The pushing unit 305 is configured to, after the second determining unit 304 determines the activity location of the controlled object according to the N video images, push the activity location to the terminal.

It can be seen that, through the video processing device described in the embodiment of the present invention, the face image of the control object sent by the terminal is received, the video file within the target control range is obtained, and the N image matching the face image is determined from the video file. A video image, and determine the activity place of the controlled object according to the N video images. Therefore, the activity place of the controlled object can be determined, and further, it is convenient for the user to analyze the activity rule of the controlled object.

Consistent with the above, please refer to FIG. 4 , which is a schematic structural diagram of a second embodiment of a video processing apparatus provided by an embodiment of the present invention. The video processing apparatus described in this embodiment includes: at least one input device 1000; at least one output device 2000; at least one processor 3000, such as a CPU; and memory 4000, the above-mentioned input device 1000, output device 2000, processor 3000 It is connected with the memory 4000 through the bus 5000.

Wherein, the above-mentioned input device 1000 may specifically be a touch panel, a physical button or a mouse.

The aforementioned output device 2000 may specifically be a display screen.

The above-mentioned memory 4000 may be a high-speed RAM memory, or a non-volatile memory (non-volatile memory), such as a magnetic disk memory. The above-mentioned memory 4000 is used to store a set of program codes, and the above-mentioned input device 1000, output device 2000 and processor 3000 are used to call the program codes stored in the memory 4000, and perform the following operations:

The above-mentioned processor 3000 is used for:

Receive the face image of the controlled object sent by the terminal;

Obtain video files within the control range of the target;

Determining N video images matching the face images from the video file;

An activity location of the controlled object is determined according to the N video images.

Optionally, the above-mentioned processor 3000 acquires video files within the control range of the target, including:

Obtain the control time period selected by the user;

Selecting the video files within the control time period and the target control range from the historical video library.

Optionally, the processor 3000 determines from the video file N video images that match the face image, including:

The video file is analyzed to obtain Q video images, and the Q is a positive integer;

Eliminate video images that do not contain human face images in the Q video images to obtain P video images, and the P is an integer less than or equal to the Q;

Matching the face images with the P video images respectively to obtain the P matching values;

Selecting the N matching values greater than the first preset threshold among the P matching values, and acquiring their corresponding video images.

Optionally, each video image in the N video images corresponds to a position marker, and the processor 3000, determining the activity site of the controlled object according to the N video images includes:

Divide the N video images into M categories according to the position marks, and the M is an integer less than or equal to the N;

Select a category whose number of video images in the M category is greater than a second preset threshold to obtain a K category, and use the position mark corresponding to the K category as the activity place of the controlled object.

Optionally, the above-mentioned processor 3000 is further specifically configured to:

Pushing the event location to the terminal.

An embodiment of the present invention also provides a computer storage medium, wherein the computer storage medium can store a program, and when the program is executed, some or all steps of any video processing method described in the above method embodiments are included.

Although the present invention has been described in conjunction with various embodiments herein, in the process of implementing the claimed invention, those skilled in the art can understand and Other variations of the disclosed embodiments are implemented. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that these measures cannot be combined to advantage.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, devices (devices), or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. The computer program is stored/distributed on suitable media, supplied with or as part of other hardware, and may also take other forms of distribution, such as via the Internet or other wired or wireless telecommunication systems.

The present invention is described with reference to flowcharts and/or block diagrams of methods, apparatus (device) and computer program products according to embodiments of the present invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

Although the invention has been described in conjunction with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made therein without departing from the spirit and scope of the invention. Accordingly, the specification and drawings are merely illustrative of the invention as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the invention. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims (10)

1. A video processing method, characterized in that, comprising: Receive the face image of the controlled object sent by the terminal; Obtain video files within the control range of the target; Determining N video images matching the face images from the video file; An activity location of the controlled object is determined according to the N video images. 2. The method according to claim 1, characterized in that said acquiring video files within the range of target control includes: Obtain the control time period selected by the user; Selecting the video files within the control time period and the target control range from the historical video library. 3. The method according to any one of claims 1 and 2, wherein said determining N video images matching said face images from said video file comprises: The video file is analyzed to obtain Q video images, and the Q is a positive integer; Eliminate video images that do not contain human face images in the Q video images to obtain P video images, and the P is an integer less than or equal to the Q; Matching the face images with the P video images respectively to obtain the P matching values; Selecting the N matching values greater than the first preset threshold among the P matching values, and acquiring their corresponding video images. 4. The method according to any one of claims 1 and 2, wherein each video image in the N video images corresponds to a position marker; The determining the activity place of the controlled object according to the N video images includes: Divide the N video images into M categories according to the position marks, and the M is an integer less than or equal to the N; Select a category whose number of video images in the M category is greater than a second preset threshold to obtain a K category, and use the position mark corresponding to the K category as the activity place of the controlled object. 5. The method according to any one of claims 1 or 2, characterized in that, after determining the activity site of the controlled object according to the N video images, the method further comprises: Pushing the event location to the terminal. 6. A video processing device, characterized in that, comprising: a receiving unit, configured to receive the face image of the controlled object sent by the terminal; an acquisition unit, configured to acquire video files within the range of target deployment; A first determining unit, configured to determine N video images matching the human face image from the video file; The second determining unit is configured to determine an activity location of the controlled object according to the N video images. 7. The video processing device according to claim 6, wherein the acquiring unit comprises: An acquisition module, configured to acquire the control time period selected by the user; The first selection module is used to select video files within the control time period and the target control range from the historical video library. 8. The video processing device according to any one of claims 6 or 7, wherein the first determining unit comprises: An analysis module, configured to analyze the video file to obtain Q video images, where the Q is a positive integer; The elimination module is used to eliminate video images that do not contain human face images in the Q video images to obtain P video images, and the P is an integer less than or equal to the Q; A matching module, configured to match the face images with the P video images respectively to obtain the P matching values; The second selecting module is configured to select the N matching values greater than the first preset threshold among the P matching values, and acquire their corresponding video images. 9. The video processing device according to any one of claims 6 or 7, wherein each video image in the N video images corresponds to a position marker; The second determination unit includes: A division module, configured to divide the N video images into M categories according to position marks, and the M is an integer less than or equal to the N; The third selection module is configured to select a category whose video image quantity is greater than a second preset threshold in the M category, obtain a K category, and use the position mark corresponding to the K category as the activity place of the controlled object. 10. The video processing device according to any one of claims 6 or 7, wherein the video processing device further comprises: A pushing unit, configured to push the activity location of the controlled object to the terminal after the second determining unit determines the activity location of the controlled object according to the N video images.