CN111447403B

CN111447403B - Video display method, device and system

Info

Publication number: CN111447403B
Application number: CN201910040917.7A
Authority: CN
Inventors: 李文伟
Original assignee: Hangzhou Hikvision Digital Technology Co Ltd
Current assignee: Hangzhou Hikvision Digital Technology Co Ltd
Priority date: 2019-01-16
Filing date: 2019-01-16
Publication date: 2021-07-30
Anticipated expiration: 2039-01-16
Also published as: CN111447403A

Abstract

The embodiment of the application provides a video display method, a video display device and a video display system. The graphical user interface includes: the video display window is positioned on the left side of the graphical user interface and is used for displaying video frames sent by the camera in real time; the video frame comprises N targets; the window list is positioned on the right side of the graphical user interface and used for displaying the alarm information which is sent by the camera and is associated with each target; the alarm information associated with each target comprises track information of the target and an image containing the target; and the playing control is positioned at the upper right side of the video display window and used for displaying the human face image or the human body image included in the alarm information. The server selects the track information M of the target D₂And displaying the video frame in an overlapping mode. By applying the technical scheme provided by the embodiment of the application, the workload of installation and debugging of the camera during monitoring is reduced, the performance requirement on the server is reduced, and the monitoring cost is reduced.

Description

Video display method, device and system

Technical Field

The present application relates to the field of video monitoring technologies, and in particular, to a video display method, device, and system.

Background

Currently, a scene is monitored by a plurality of cameras. Specifically, a plurality of cameras are deployed in the scene, the monitoring area of each camera is a partial area of the scene, and the monitoring areas of the plurality of cameras form the whole scene. Each camera collects video frames, carries out face recognition on the video frames, and sends track information of a target, the recognized face and the video frames to a background server. And the background server splices the monitoring videos generated by the cameras to obtain a monitoring video frame of the whole scene. In addition, the background server needs to compare faces recognized by the cameras, determine whether the faces are the same target, combine track information of the same target, and then display the track information on the monitoring video.

Therefore, in order to monitor a scene to obtain a high-definition target video frame, a plurality of cameras need to be installed, and each camera needs to be debugged, so that the monitoring areas of the cameras have overlapping parts, and the installation and debugging workload is large. In addition, the server needs to perform processing such as monitoring video frame splicing and track information, so that the performance requirement on the server is high, and the monitoring cost is high.

Disclosure of Invention

An object of the embodiments of the present application is to provide a video display method, device, and system, so as to reduce workload of installation and debugging of a camera during monitoring, reduce performance requirements on a server, and reduce monitoring cost. The specific technical scheme is as follows:

in order to achieve the above object, an embodiment of the present application provides a video display method, which is applied to a server having a graphical user interface, where the graphical user interface includes:

the video display window is positioned on the left side of the graphical user interface and is used for displaying video frames sent by the camera in real time; the video frame comprises N targets, wherein N is a positive integer and is more than or equal to 1;

a window list located on the right side of the graphical user interface for displaying alert information associated with each target sent by the camera; the alarm information associated with each target comprises track information of the target and an image containing the target, the track information of the target comprises at least one image coordinate of the target, and the image containing the target comprises a face image and/or a human body image of the target;

the playing control is positioned at the upper right side of the video display window and used for displaying the human face image or the human body image included in the alarm information;

the method comprises the following steps:

receiving externally input alarm information M aiming at display in the window list₁A selection instruction of (1);

acquiring the alarm information M₁Track information M included₂Said track information M₂At least one image coordinate comprising a target D;

and overlaying the at least one image coordinate on the video frame for display.

Optionally, the alarm information M displayed in the window list is received and input from the outside₁After the selecting instruction, the method further comprises:

acquiring the alarm information M₁Including face images or body images;

and controlling the playing control to display the acquired face image or human body image.

Optionally, the window list is specifically configured to display a face image or a human body image included in the alarm information.

Optionally, the alarm information M input from the outside and displayed in the window list is received₁The step of selecting an instruction of (1), comprising:

receiving an externally input image T for display in the window list₁A selection instruction of (1);

the obtaining of the alarm information M₁Track information M included₂The method comprises the following steps:

determining the image T₁A first global identity of;

determining track information M corresponding to the first global identification according to the corresponding relation between the global identification and the track information stored in advance₂。

Optionally, the step of superimposing the at least one image coordinate on the video frame for display includes:

and superposing the at least one image coordinate on the video frame in a point or connecting line mode for display.

Optionally, the track information M₂Further comprising an elapsed time for the object D to pass each of the at least one image coordinate and a dwell time for the object D at each of the at least one image coordinate; the method further comprises the following steps:

and superposing each elapsed time and the stay time corresponding to the target D to the corresponding image coordinate on the video frame for displaying.

Optionally, after the at least one image coordinate is superimposed on the video frame for display, the method further includes:

the object D is marked on the video frame at the latest image coordinate of the at least one image coordinate.

In order to achieve the above object, an embodiment of the present application further provides a video display apparatus, which is applied to a server having a graphical user interface, where the graphical user interface includes:

the device comprises:

a receiving module, configured to receive externally input alarm information M displayed in the window list₁A selection instruction of (1);

an obtaining module for obtaining the alarm information M₁Track information M included₂Said track information M₂At least one image coordinate comprising a target D;

and the superposition module is used for superposing the at least one image coordinate on the video frame for display.

In order to achieve the above object, an embodiment of the present application further provides a video display system, which includes a server having a graphical user interface, a plurality of sensor cameras connected to the server;

the multi-sensor camera includes: the large-field-of-view lens assembly comprises a large-field-of-view lens assembly and a large-field-of-view sensor corresponding to the large-field-of-view lens assembly; at least one small-field-of-view lens component and a small-field-of-view sensor corresponding to the small-field-of-view lens component; the field angle of the large-field lens assembly is larger than that of the small-field lens assembly, and for the same target, the definition of the large-field sensor is smaller than that of the small-field sensor;

the processor of the multi-sensor camera sends a large-view-field video frame generated by the large-view-field sensor to the server in real time, and analyzes the large-view-field video frame and a small-view-field video frame generated by the small-view-field sensor to obtain an image including a target and track information of the target; the large-view-field video frame comprises N targets, wherein N is a positive integer and is more than or equal to 1;

the graphical user interface includes:

a video display window, located on the left side of the graphical user interface, for displaying video frames sent by the multiple sensor cameras in real time;

the server is used for receiving externally input alarm information M aiming at the display in the window list₁A selection instruction of (1); acquiring the alarm information M₁Track information M included₂Said track information M₂At least one image coordinate comprising a target D; and overlaying the at least one image coordinate on the video frame for display.

Optionally, the processor of the multiple sensor camera is further configured to:

performing human body analysis on the large-view-field video frame;

if the large-field-of-view video frame obtained through analysis comprises a first target, determining a first coordinate of the first target and a first global identifier of the first target;

and sending the corresponding relation of the first coordinate, the first global identification and the large-view-field video frame to the server.

performing face analysis or head and shoulder analysis or human body analysis on the small view field video frame;

if the small view field video frame obtained through analysis comprises a second target, determining a second coordinate of the second target;

detecting whether the distance between the second coordinate and the first coordinate is smaller than a first preset distance threshold value or not to obtain a first detection result;

and if the first detection result is positive, sending the corresponding relation between the first global identification and the small-view-field video frame to the server.

acquiring first characteristic information of the first target and second characteristic information of the second target;

detecting whether the similarity between the first characteristic information and the second characteristic information is greater than a preset similarity threshold value or not to obtain a second detection result;

if the first detection result is yes, the step of sending the corresponding relationship between the first global identifier and the small-field video frame to the server includes:

and if the first detection result is yes and the second detection result is yes, sending the corresponding relation between the first global identification and the small-view-field video frame to the server.

Optionally, the step of detecting whether the distance between the second coordinate and the first coordinate is smaller than a first preset distance threshold to obtain a first detection result includes:

mapping the first coordinate to a reference coordinate system to obtain a first reference coordinate;

mapping the second coordinate to a reference coordinate system to obtain a second reference coordinate;

calculating a physical distance between the first reference coordinate and the second reference coordinate;

if the physical distance obtained by calculating the continuous preset times is smaller than a preset distance threshold, determining that a first detection result is that the distance between the second coordinate and the first coordinate is smaller than the preset distance threshold; otherwise, determining that the distance between the second coordinate and the first coordinate is not smaller than a preset distance threshold value according to the first detection result.

detecting whether the distance between the first coordinate and the newly recorded coordinate of the first target is greater than a second preset distance threshold value or not;

if so, recording the first coordinate;

when the second target is detected to leave the field range of the small-field lens assembly corresponding to the small-field video frame, generating track information for the first target according to the recorded coordinates of the first target, and sending the corresponding relation between the first global identification and the track information for the first target to the server, wherein the first target and the second target are the same target.

In order to achieve the above object, an embodiment of the present application further provides a server, including a processor and a memory;

the memory is used for storing a computer program;

the processor is used for executing the program stored in the memory to realize any step of the video display method.

To achieve the above object, an embodiment of the present application further provides a machine-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements any step of the above video display method.

In the technical scheme provided by the embodiment of the application, one camera acquires video frames and images containing the target, wherein the images containing the target comprise face images and/or human body images of the target. The server displays video frames in a video display window, displays alarm information in a window list, and displays face images or human body images included in the alarm information in the playing control. At the moment, for a scene, only one camera is installed, and debugging of a plurality of cameras for meeting monitoring requirements is not needed, so that the workload of installation and debugging of the cameras during monitoring is reduced while scene monitoring is realized. In addition, the server does not need to splice the monitoring videos, does not need to merge track information and the like, and reduces the performance requirement on the server.

Of course, it is not necessary for any product or method of the present application to achieve all of the above-described advantages at the same time.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments or related technologies of the present application, the drawings needed to be used in the description of the embodiments or related technologies are briefly introduced below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic deployment diagram of a monitoring scenario provided by the related art;

fig. 2 is a schematic diagram of a first structure of a video display system according to an embodiment of the present application;

FIG. 3 is a schematic structural diagram of a graphical user interface provided in an embodiment of the present application;

FIG. 4 is a schematic view of a field of view range of a large field of view lens assembly and a field of view range of a small field of view lens assembly according to an embodiment of the present disclosure;

FIG. 5 is a schematic processing flow diagram of a large-field-of-view video frame according to an embodiment of the present application;

fig. 6 is a schematic diagram of a second structure of a video display system according to an embodiment of the present application;

FIG. 7 is a diagram illustrating a video frame presentation of a graphical interface provided by an embodiment of the present application;

FIG. 8 is a flowchart illustrating a process for processing a small-field video frame according to an embodiment of the present application;

fig. 9 is a schematic flowchart of a video display method according to an embodiment of the present application;

FIG. 10a is a first schematic diagram of track information display provided in an embodiment of the present application;

FIG. 10b is a second exemplary diagram of track information display provided in the embodiments of the present application;

FIG. 10c is a third exemplary diagram of track information display provided in the embodiments of the present application;

fig. 11 is a schematic structural diagram of a video display apparatus according to an embodiment of the present application;

fig. 12 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

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 only a part of the embodiments of the present application, and not all of the 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.

Currently, the monitoring scenario shown in fig. 1 includes: a plurality of cameras 100 and a server 101. When monitoring a scene, each camera 100 monitors a part of the area of the scene and collects a monitoring video frame. After the camera 100 acquires the surveillance video frame, it performs face recognition on the surveillance video frame and sends the recognition result and the surveillance video frame to the server 101. The server 101 splices the surveillance video frames acquired by the cameras 100 to obtain a surveillance video frame of the whole scene. In addition, the server 101 compares the faces recognized by the cameras 100, and if the faces are the same target, records the corresponding camera 100 and the time point of acquisition, and obtains the track of the target.

As can be seen from the above, in order to monitor a scene to obtain a high-definition target video frame, and facilitate the server 101 to obtain the monitored video frame of the whole scene, a plurality of cameras 100 need to be installed, and each camera 100 is debugged, so that the monitoring areas of the cameras 100 have overlapping portions, which makes the installation and debugging workload large. In addition, the server 101 needs to perform processing such as monitoring video frame splicing and track information, and has high requirements on the performance of the server and high monitoring cost.

In order to reduce the workload of installation and debugging of a camera during monitoring, reduce the performance requirement on a server and reduce the monitoring cost, the embodiment of the application provides a video display system. As shown in fig. 2, the video display system includes a server 10 having a graphic user interface, a plurality of sensor cameras 11 connected to the server 10;

the multi-sensor camera 11 includes: a large-field-of-view lens assembly 20 and a large-field-of-view sensor 21 corresponding to the large-field-of-view lens assembly 20, and at least one small-field-of-view lens assembly 22 and a small-field-of-view sensor 23 corresponding to the small-field-of-view lens assembly 22. Wherein the field angle of the large-field lens assembly 20 is larger than that of the small-field lens assembly 22, and the resolution of the large-field sensor 21 is smaller than that of the small-field sensor 23 for the same object. It can also be understood that for the same object, the pixels of the large-field video frame generated by the large-field sensor 21 are smaller than the pixels of the small-field video frame generated by the small-field sensor 23.

The processor 24 of the multi-sensor camera 11 sends the large-field video frame generated by the large-field sensor 21 to the server 10 in real time, and analyzes the large-field video frame and the small-field video frame generated by the small-field sensor 23 to obtain an image including a target and track information of the target; the large-field-of-view video frame comprises N targets, wherein N is a positive integer and is more than or equal to 1.

The graphical user interface of the server 10, as shown in fig. 3, comprises: a video display window 300, a window list 320, and a play control 310.

One of the video display windows 300 is located on the left side of the gui, and is used for displaying the video frames sent by the multiple sensor cameras 11 in real time. Here, the video frame may be the above-described large-field video frame or small-field video frame.

A window list 320 located on the right side of the graphical user interface for displaying the alarm information associated with each target sent by the camera; the alarm information associated with each target comprises track information of the target and an image containing the target, the track information of the target comprises at least one image coordinate of the target, and the image containing the target comprises a face image and/or a human body image of the target.

And the playing control 310 is positioned at the upper right side of the video display window and is used for displaying the human face image or the human body image included in the alarm information.

A server 10 for receiving externally input alarm information M displayed in the window list₁A selection instruction of (1); obtaining alarm information M₁Track information M included₂Track information M₂At least one image coordinate comprising a target D; and at least one image coordinate is superposed on the video frame for display.

In one embodiment, the large field sensor 21 may be a sensor with a resolution of 200W or 400W pixels, which is effective in low illumination, and the small field sensor 23 may be a sensor with a resolution of 400W or 800W pixels.

In one example, different small field-of-view sensors 23 may be used with the same resolution. For example, the camera includes 2 small field-of-view sensors 23, both of which 23 are 400W pixel sensors.

In another example, different small field-of-view sensors 23, sensors of different resolutions may be employed. For example, the camera includes 2 small field-of-view sensors 23, where one small field-of-view sensor 23 is a 400W pixel sensor and one small field-of-view sensor 23 is an 800W pixel sensor.

In one embodiment of the present application, the multi-sensor camera 11 may further include an infrared fill-in light assembly. The small-field-of-view lens assembly 22 performs infrared light supplement using an infrared light supplement assembly. Therefore, the small field sensor can achieve a relatively uniform effect on video frames generated under forward light, backward light and night scenes, and can be used for high-definition large image acquisition of targets.

In one embodiment of the present application, the multi-sensor camera 11 may further include a white light supplement assembly. The large field lens assembly 20 performs white light supplement using the white light supplement assembly. Therefore, the video frame generated by the large-view-field sensor can achieve a full-color effect, and key information such as target dressing color and the like can be provided at night.

In one embodiment of the present application, to ensure complete detection of the target, as shown in fig. 4, the field of view range of the large-field-of-view lens assembly 20 includes part or all of the field of view range of the small-field-of-view lens assembly 22, and the field of view range of the large-field-of-view lens assembly 20 includes a width of the part of the field of view range of the small-field-of-view lens assembly 22, that is, a width of a field-of-view overlapping portion, which is greater than a maximum width threshold of the target. Here, the maximum width threshold of the target may be empirically set. For example, if a small-field video frame is used for face analysis, and the maximum width threshold of a face is 100 pixels, the field range of the large-field lens assembly 20 includes a field range portion of the small-field lens assembly 22 having a width greater than 100 pixels.

In one embodiment of the present application, to reduce image skew due to temporal acquisition inconsistencies, the temporal skew of the large field-of-view sensor 21 and the at least one small field-of-view sensor 23 is not greater than the duration of one video frame. In one example, to reduce the time offset of the video frames generated by the different sensors, the large field-of-view sensor 21 and the at least one small field-of-view sensor 23 may use the same clock source. In another example, the large field-of-view sensor 21 and the at least one small field-of-view sensor 23 may use tightly synchronized clock sources.

In the embodiment of the present application, processor 24 may use different processing logic for processing video frames generated by different sensors. For example, the processor 24 performs human body analysis on the large-field video frames generated by the large-field sensor 21, and performs face analysis or head-shoulder analysis or human body analysis on the small-field video frames generated by the small-field sensor 23.

In one example, the camera may include multiple small-field-of-view components 22 and small-field-of-view sensors 23 corresponding to small-field-of-view components 22, and the small-field video frames generated by processor 24 for different small-field-of-view sensors 23 may be processed using the same processing logic. For example, the camera includes 2 small-field sensors 23, and the processor 24 performs face analysis on both small-field video frames generated by the two small-field sensors 23.

In another example, the camera may include multiple small-field-of-view lens assemblies 22 and small-field-of-view sensors 23 corresponding to small-field-of-view lens assemblies 22, and processor 24 may process small-field video frames generated by different small-field-of-view sensors 23 using different processing logic. For example, the camera includes 2 small-field sensors 23, and for a small-field video frame generated by one of the small-field sensors 23, the processor 24 performs face analysis on the small-field video frame, and for a small-field video frame generated by the other small-field sensor 23, the processor 24 performs head-shoulder analysis on the small-field video frame.

In one embodiment of the present application, the processing flow of the large-field-of-view video frames by processor 24 is illustrated with reference to fig. 5 and may include the following steps.

Step 501, performing human body analysis on the large-view-field video frame.

In an alternative embodiment, the processor 24 performs human body analysis on each frame of the large-field video frames generated by the large-field sensor 21 to detect whether the first target exists in the large-field video frames. In this way, processor 24 may discover the first target in a timely manner. The number of objects in a frame of large-field video frame may be one or more. Here, the first object is described as an example, and is not limited.

In another alternative embodiment, the processor 24 performs human body analysis on one frame of large-view-field video frames generated by the large-view-field sensor 21 every preset time interval, that is, performs human body analysis on the large-view-field video frames every preset number of frames, and detects whether the first target exists in the large-view-field video frames. Thus, the load on the processor 24 is reduced, and the processing efficiency of the processor 24 is improved.

In one embodiment of the present application, to facilitate human body analysis of large field-of-view video frames, a high performance computing module 25 is also included in the camera, as shown in fig. 6. Processor 24 feeds the large field of view video frames into high performance computing module 25. The high performance computing module 25 performs human body analysis on the large field of view video frames and feeds back the analysis results to the processor 24.

Step 502, if the large-field video frame obtained through analysis includes a first target, determining a first coordinate of the first target and a first global identifier of the first target. And the first coordinate is the coordinate of the first target in the large-field-of-view video frame. The first coordinates may be coordinates of a body center of the first object in the large-field-of-view video frame, may be coordinates of a head of the first object in the large-field-of-view video frame, and may also be coordinates of shoulders of the first object in the large-field-of-view video frame.

After the processor 24 performs human body analysis on the large-view-field video frame, if it is determined that the large-view-field video frame includes the first target, a first coordinate of the first target in the large-view-field video frame is determined, and a first global identifier of the first target is determined.

In an alternative embodiment, processor 24 may determine the first global identification as follows.

At step a11, processor 24 obtains first coordinates of a first target.

At step a12, processor 24 detects whether a first reference target exists in the target from the last analysis of the large field-of-view video frame. If so, step a13 is performed. If not, step a14 is executed.

Wherein the first reference target is: the processor 24 predicts the target, in which the distance between the coordinate in the large-view-field video frame analyzed this time and the first coordinate is smaller than the preset target distance threshold, in the target obtained by analyzing the large-view-field video frame last time. The target preset distance threshold value can be set according to the requirement.

At step a13, processor 24 obtains the global identification of the first reference target as the first global identification of the first target.

In step a14, processor 24 assigns a global tag to the first target as the first global tag.

In an alternative embodiment, to accurately determine the first global identification of the first target, processor 24 may determine the first global identification as follows.

At step a21, processor 24 obtains first coordinates and first feature information of a first object. Here, the characteristic information may include, but is not limited to, hair color, hair length, jacket color, trousers color, and movement tendency, etc.

At step a22, processor 24 detects whether a first reference target exists in the target from the last analysis of the large field-of-view video frame. If so, step a23 is performed. If not, step a25 is executed.

In step a23, the processor 24 detects whether the similarity between the feature information of the first reference target and the first feature information is greater than a preset similarity threshold of the target. If yes, go to step a 24. If not, step a25 is executed.

In the embodiment of the present application, the execution sequence of step a22 and step a23 is not limited. Only the distance between the target and the first coordinate in the large-view-field video frame analyzed this time is smaller than the preset target distance threshold value, and the similarity between the characteristic information of the target and the first characteristic information is greater than the preset target similarity threshold value, the step a24 is executed. Otherwise, step 25 is performed.

In the embodiment of the present application, the first reference target may be one or more.

At step a24, processor 24 takes the global identification of the first reference target as the first global identification of the first target.

In one embodiment, if there are a plurality of first reference targets, the processor 24 calculates the similarity between the feature information of each first reference target and the first feature information, and detects whether the maximum similarity among the calculated similarities is greater than a preset similarity threshold of the target. If so, the processor 24 uses the global identifier of the first reference target corresponding to the maximum similarity as the first global identifier of the first target.

In step a25, processor 24 assigns a global tag to the first target as the first global tag.

Here, the first coordinate of the first target is considered, and the first characteristic information of the first target is also considered, so that the accuracy of determining the first global identifier is improved.

Step 503, sending the corresponding relationship between the first coordinate, the first global identifier and the large-field-of-view video frame to the server 10.

In an alternative embodiment, the processor 24 may directly send the correspondence between the first coordinate, the first global identifier, and the large-field-of-view video frame to the server.

In another alternative embodiment, the step of sending, by the processor 24, the correspondence between the first coordinate, the first global identifier and the large-field-of-view video frame to the server 10 may specifically include.

In step b11, processor 24 captures a first region of the large-field video frame in which the first object is located.

In this embodiment of the application, the intercepted first region may include a face image of the first target, or may also be an image of a human body including the first target.

In step b12, processor 24 encodes the first region at the resolution of the large field of view video frame to obtain a first target image.

After the processor 24 obtains the first region, the first region is directly encoded to obtain a first target image.

For example, the original resolution of the large-field video frame is 400W pixels, and the first region of the large-field video frame that is extracted by processor 24 is 200 pixels. The processor 24 encodes the first region by 400W pixels to obtain a first target image, i.e. an image of the first target image with a resolution of 200 pixels. Therefore, the server can play the first target image according to 400W pixels, and the server can acquire the clear first target image.

Step b13, the processor 24 encodes the large-field video frame according to a preset first resolution to obtain an encoded large-field video frame; the first resolution is less than or equal to the resolution of the large field of view image.

The processor 24 encodes the large-field-of-view video frame according to a preset first resolution to obtain an encoded large-field-of-view video frame, that is, reduces the resolution of the large-field-of-view video frame to the first resolution.

For example, the original resolution of a large field of view video frame is 400W pixels and the first resolution is 100W pixels. The processor 24 streams the large-field-of-view video frame according to 100W pixels, that is, encodes the large-field-of-view video frame according to 100W pixels to obtain an encoded large-field-of-view video frame, and reduces the resolution of the large-field-of-view video frame to 100W pixels. Thus, the server 10 can play the enlarged field of view video frame by 100W pixels. Due to the fact that the pixels of the large-view-field video frame are reduced, the data volume of the large-view-field video frame is reduced, and the transmission efficiency is improved.

In the embodiment of the present application, the execution order of step b12 and step b13 is not limited.

b14, sending the first coordinate, the first global mark, the corresponding relation between the encoded large-field video frame and the first target image to the server 10.

In an embodiment of the present application, if the processor 24 performs human body analysis on the large-view-field video frame to obtain no first target, the processor 24 may discard the large-view-field video frame and does not send the large-view-field video frame to the server, so as to save network resources.

In the embodiment of the present application, the server 10 receives the large-field video frame, and may display the large-field video frame on the video display window 300. At this time, the server 10 may mark the first target at the first coordinate. For example, the server 10 may mark the first object with a rectangular box. The first object is marked with a rectangular box at the P position as shown in fig. 7. Therefore, the user can conveniently and intuitively see the position of the target. The server 10 receives the first target image, and may display the first target image in the play control 310, or may display the first target image in the video display window 32.

In an embodiment of the present application, for the small-field video frame generated by each small-field sensor 23, the processing flow of the small-field video frame by the processor 24 can be as shown in fig. 8, and includes the following steps.

Step 801, performing face analysis or head and shoulder analysis or human body analysis on the small-view video frame.

In an alternative embodiment, the processor 24 performs a face analysis or a head-shoulder analysis or a human body analysis on each of the small-field video frames generated by the small-field sensor 23 to detect whether the second target exists in the small-field video frames. In this way, processor 24 may discover the second target in a timely manner. The number of objects in a frame of a small-field image may be one or more. Here, the second object is described as an example, and is not limited.

In another alternative embodiment, the processor 24 performs face analysis or head-shoulder analysis or human body analysis on one frame of small-field video frames generated by the small-field sensor 23 every preset time interval, that is, performs face analysis or head-shoulder analysis or human body analysis on the small-field video frames every preset number of frames of small-field video frames, and detects whether the second target exists in the small-field video frames. Thus, the load on the processor 24 is reduced, and the processing efficiency of the processor 24 is improved.

The preset interval duration for performing face analysis, head and shoulder analysis or human body analysis on the small-field video frame is the same as the preset interval duration for performing human body analysis on the large-field video frame, so that image deviation caused by time inconsistency is reduced.

In one embodiment of the present application, to facilitate face analysis or head-shoulder analysis or body analysis of small-field video frames, a high-performance computing module 25 is also included in the camera, as shown in fig. 6. Processor 24 feeds the small-field video frames to high-performance computation module 25. The high-performance calculation module 25 performs face analysis, head and shoulder analysis, or human body analysis on the small-view video frame, and feeds back the analysis result to the processor 24.

Step 802, if the small-field video frame obtained through analysis includes a second target, determining a second coordinate of the second target. And the second coordinate is the coordinate of the second target in the small-field video frame. The second coordinates may be coordinates of a center of a human body of the second object in the small-field video frame, may be coordinates of a head of the second object in the small-field video frame, and may also be coordinates of shoulders of the second object in the small-field video frame.

After the processor 24 performs face analysis, head-shoulder analysis or human body analysis on the small-view video frame, if it is determined that the small-view video frame includes the second target, the second coordinate of the second target in the small-view video frame is determined.

Step 803, detecting whether the distance between the second coordinate and the first coordinate is smaller than a preset distance threshold value, and obtaining a first detection result.

The first detection result may be that the distance between the second coordinate and the first coordinate is smaller than a preset distance threshold. The first detection result may also be negative, that is, the first detection result is that the distance between the second coordinate and the first coordinate is not less than the preset distance threshold.

In one embodiment of the present application, to facilitate determining whether the distance between the second coordinate and the first coordinate is less than a preset distance threshold, a reference coordinate system may be preset. The processor 24 maps the first coordinate to a reference coordinate system to obtain a first reference coordinate; and mapping the second coordinate to a reference coordinate system to obtain a second reference coordinate. The processor 24 calculates a physical distance between the first reference coordinate and the second reference coordinate. If the physical distance calculated by the continuous preset times is smaller than the preset distance threshold, the processor 24 may determine that the first detection result is that the distance between the second coordinate and the first coordinate is smaller than the preset distance threshold. Otherwise, the processor 24 may determine that the first detection result is that the distance between the second coordinate and the first coordinate is not less than the preset distance threshold.

In the embodiment of the application, the large-field sensor 21 and the small-field sensor 23 are calibrated, and the first coordinate and the second coordinate are converted into a reference coordinate system. Here, in calibration, distortion parameters of the large field sensor 21 and the small field sensor 23 are considered to correct distortion of the large field sensor 21 and the small field sensor 23 themselves.

In an embodiment of the present application, in order to improve the detection efficiency and improve the accuracy of the detection result, when the processor 24 detects whether the distance between the second coordinate and the first coordinate is smaller than the preset distance threshold, the generation time of the large-field video frame corresponding to the first coordinate is the same as the generation time of the small-field video frame corresponding to the second coordinate, or the time deviation is not greater than the duration of one video frame.

Step 804, if the first detection result is yes, the corresponding relationship between the first global identifier and the small-field video frame is sent to the server 10.

In this embodiment of the application, if the first detection result is yes, the processor 24 determines that the first target and the second target are the same target, and determines that the global identifier of the second target is the first global identifier of the first target. The small-view-field video frame is associated with the large-view-field video frame through the global identification, so that the server can conveniently analyze and process the image.

In one embodiment of the present application, to accurately determine whether the first target and the second target are the same target, the processor 24 may further obtain first characteristic information of the first target and second characteristic information of the second target. The processor 24 detects whether the similarity between the first characteristic information and the second characteristic information is greater than a preset similarity threshold. And if the first detection result is positive and the second detection result is negative, determining that the first target and the second target are the same target, determining that the global identifier of the second target is the first global identifier of the first target, and sending the corresponding relation between the first global identifier and the small-view video frame to the server. The first characteristic information and the second characteristic information include, but are not limited to, information such as movement tendency, hair color, and hair length.

In an embodiment of the present application, the step of sending, by the processor 24, the correspondence between the first global identifier and the small-field video frame to the server may specifically include.

At step c11, processor 24 intercepts a second region of the small-field video frame where the second object is located.

In this embodiment of the application, the intercepted second region may include a face image of the second target, or may also be an image of a human body including the second target.

In step c12, processor 24 encodes the second region at the resolution of the small-field video frame to obtain a second target image.

After the processor 24 obtains the second region, the second region is directly encoded to obtain a second target image.

For example, the original resolution of the small-field video frame is 800W pixels, the server-fetched resolution is 200W, and the second region of the small-field video frame that is extracted by processor 24 is 200 pixels. The processor 24 encodes the second region by 800W pixels to obtain a second target image, i.e. an image of the second target image with a resolution of 200 pixels. Thus, the server can take the stream according to 200W, and simultaneously obtain the target graph with high definition resolution at 800W.

Step c13, the processor 24 encodes the small-field video frame according to a preset second resolution to obtain an encoded small-field video frame; the second resolution is less than or equal to the resolution of the small-field video frame.

The processor 24 encodes the small-field video frame according to a preset second resolution to obtain an encoded small-field video frame, that is, reduces the resolution of the small-field video frame to the second resolution.

For example, the original resolution of the small-field video frame is 800W pixels, and the second resolution is 100W pixels. The processor 24 fetches a stream of the small-field video frame according to 100W pixels, that is, encodes the small-field video frame according to 100W pixels to obtain an encoded small-field video frame, and reduces the resolution of the small-field video frame to 100W pixels. Thus, the server 10 can play the small-field video frame by 100W pixels. Because the pixels of the small-view video frame are reduced, the data volume of the small-view video frame is reduced, and the transmission efficiency is improved.

In the embodiment of the present application, the execution order of step c12 and step c13 is not limited.

And c14, sending the corresponding relation between the second coordinate, the first global identifier, the encoded small-field video frame and the second target image to the server 10.

In the embodiment of the present application, the processor 24 processes the small-view video frame to obtain the encoded small-view video frame and the second target image, and sends the second coordinate, the first global identifier, and the corresponding relationship between the encoded small-view video frame and the second target image to the server. The small-field video frame is associated with the large-field video frame through the global identifier, so that the server 10 can analyze and process the video frames conveniently.

In an embodiment of the present application, if the processor 24 does not obtain the second target by performing human body analysis on the small-field video frame, the processor 24 may discard the small-field video frame and does not send the small-field video frame to the server, so as to save network resources.

In the embodiment of the present application, the server 10 receives the small-field video frame, and may display the small-field video frame in the video display window 300. At this time, the server 10 may mark the second object at the second coordinate, for example, the server 10 may mark the second object with a rectangular frame. After receiving the second target image, the server 10 may display the second target image in the play control 310, or may display the second target image in the video display window 300.

The server processes the small-view-field video frame and the second target image in the mode, so that a user can conveniently and visually check the position of the target.

In an embodiment of the present application, for a small-field-of-view lens component 22, the processor 24 detects a second object from a small-field-of-view video frame generated by a small-field sensor corresponding to the small-field-of-view lens component, and after a second area where the second object is located is intercepted from the small-field-of-view video frame, calculates a composite score of the second area according to the definition of the second area intercepted this time and the posture of the second object in the second area intercepted this time. Wherein, the higher the definition is, the higher the similarity between the gesture and the preset gesture is, the higher the comprehensive score is. The preset pose may be a frontal face pose of the human face.

The processor 24 compares the comprehensive score of the second region intercepted this time with the recorded comprehensive score of the small-view-field high-definition image to obtain a second image with a high comprehensive score. Wherein the small-field high-definition image comprises a second target. The processor 24 updates the recorded small-field high-definition image to a second image.

In an alternative embodiment, if the second region obtained by the current capturing is the first region including the second target generated by the small-field-of-view sensor 23 corresponding to the small-field-of-view lens assembly, the processor 24 may directly determine the second region obtained by the current capturing as the second image, and update the recorded small-field-of-view high-definition image into the second image obtained by the current capturing.

If the processor 24 analyzes and obtains the second target from the small-field-of-view video frame generated by the small-field-of-view sensor 23, when it is detected that the second target leaves the field range of the small-field-of-view lens assembly 22 corresponding to the small-field-of-view video frame (the small-field-of-view lens assembly 22 corresponding to the small-field-of-view sensor 23), the processor 24 sends the corresponding relationship between the first global identifier and the small-field-of-view high-definition image to the server.

In an embodiment of the present application, for one large-field lens assembly 20, the processor 24 detects a first object from a large-field video frame generated by a large-field sensor corresponding to the large-field lens assembly, and after a first region where the first object is located is intercepted from the large-field video frame, calculates a composite score of the first region according to the definition of the intercepted first region and the posture of the first object in the intercepted first region. Wherein, the higher the definition is, the higher the similarity between the gesture and the preset gesture is, the higher the comprehensive score is. The preset pose may be a frontal face pose of the human face.

The processor 24 compares the comprehensive score of the intercepted first area with the recorded comprehensive score of the large-view-field high-definition image to obtain a first image with a high comprehensive score. Wherein the large field of view high definition image includes a first target. The processor 24 updates the recorded large field of view high definition image to the first image.

In an alternative embodiment, if the first region obtained by the current capturing is the first region including the first target generated by the large-field-of-view sensor 21, the processor 24 may directly determine the first region obtained by the current capturing as the first image, and update the recorded large-field-of-view high-definition image to the first image obtained by the current capturing.

If the processor 24 analyzes a second target from a small-field video frame generated by a small-field sensor 21, and the second target and the first target are the same target, when it is detected that the second target leaves the field range of the small-field lens assembly 22 corresponding to the small-field video frame (the small-field lens assembly 22 corresponding to the small-field sensor 23), the processor 24 sends the corresponding relationship between the first global identifier and the large-field high-definition image to the server 10.

In an alternative embodiment, if the processor 24 analyzes the second object from the small-field-of-view video frame generated by the small-field-of-view sensor 23, the processor 24 may further send the track information of the first object to the server when detecting that the second object leaves the small-field-of-view lens assembly 22 corresponding to the small-field-of-view video frame. The second target is the same target as the first target. In one example, the track information includes: the time that the first target passes the first coordinate and the dwell time of the first target at the first coordinate.

In an alternative embodiment, processor 24 may determine trajectory information as follows. The method specifically comprises the following steps: processor 24 detects whether the distance between the first coordinates and the most recently recorded coordinates of the first object is greater than a second predetermined distance threshold. If so, recording the first coordinate. If not, the first coordinate is not recorded. And detecting whether the second target leaves the field range of the small-field lens assembly corresponding to the generated small-field video frame or not under the condition that the second target and the first target acquired by the small-field sensor 23 are the same target. And when the second target is detected to leave the field range of the small-field lens assembly corresponding to the generated small-field video frame, generating track information aiming at the first target according to the recorded coordinates of the first target, and sending the corresponding relation between the first global identification and the track information aiming at the first target to the server.

For example, processor 24 records the coordinates x1-x2-x3 of the object S, with the most recently recorded object S being x 3. When the first coordinate x4 of the object S is acquired, the processor 24 determines whether the distance between the detection x4 and the detection x3 is greater than a second preset distance threshold. If so, the processor 24 records the first coordinate x4, i.e., the recorded coordinate of the target S is updated to x1-x2-x3-x 4. If not, processor 24 does not record the first coordinate x 4. In addition, processor 24 detects whether object S leaves the field of view of a small-field-of-view lens assembly corresponding to the generated small-field-of-view video frame. And if the target S is detected to leave the field range of a small-field lens assembly corresponding to the generated small-field video frame, generating track information aiming at the target S according to the recorded coordinates of the target S, and sending the corresponding relation between the global identification of the target S and the track information aiming at the target S to a server.

In an alternative embodiment, if it is determined that the first target matches the second target, that is, the first target and the second target are the same target, when it is detected that the second target leaves the small-field lens assembly 22 corresponding to the small-field video frame, the processor 24 may carry the small-field information, the large-field information, and the track information in an alarm message and send the alarm message to the server. Wherein the small field of view information includes: the corresponding relation between the first global identification and the small-view-field high-definition image, the corresponding relation between the first global identification and the coded small-view-field video frame, the second coordinate and the like. The large field of view information includes: the corresponding relation between the first global identification and the large-view-field high-definition image, the corresponding relation between the first global identification and the coded large-view-field video frame and the like.

If the processor 24 determines that the first target and the second target do not match, that is, the first target and the second target are not the same target, when it is detected that the second target leaves the small-field lens assembly 22 corresponding to the small-field video frame, the small-field information may be carried in an alert message and sent to the server.

In the embodiment of the present application, the server 10 receives the alarm information, and displays the alarm information in the small window list 320. For ease of viewing, the server 10 may display a small-field high-definition image or a large-field high-definition image included in the alert information when the alert information is displayed in the small window list 320. As shown in fig. 7, a plurality of monoscopic high definition images are shown in the list of widgets 320 on the right side of the graphical user interface. The server 10 may display the alarm information displayed in the small window list 320, such as the serial number of the alarm information. In the embodiment of the present application, the form of the alarm information displayed in the small window list 320 is not limited.

When the user selects one piece of alarm information, the server 10 may determine the global identifier corresponding to the alarm information, and search the corresponding small-view-field high-definition image, large-view-field high-definition image, track information, and the like through the determined global identifier. The server can show a small-view-field high-definition image or a large-view-field high-definition image in the playing control. In addition, the server 10 may also superimpose and display the trajectory of the first object in the large-field-of-view video frame displayed in the video display window 300 according to the acquired trajectory information.

Based on the video display system, the embodiment of the application provides a video display method. Referring to fig. 9, fig. 9 is a schematic flowchart of a video display method according to an embodiment of the present disclosure. The method is applied to a server with a graphical user interface. The structure of the graphical user interface can be seen with reference to fig. 3, including: a video display window 300, a window list 320, and a play control 310.

Wherein, a video display window 300 is located on the left side of the graphical user interface and is used for displaying video frames sent by the camera in real time; the video frame comprises N targets, wherein N is a positive integer and is more than or equal to 1.

A window list 320 located on the right side of the graphical user interface for displaying the alarm information associated with each target sent by the camera; the alarm information associated with each target comprises track information of the target and an image containing the target, the track information of the target comprises at least one image coordinate of the target, and the image containing the target comprises a face image and/or a human body image of the target. The image coordinates are: the coordinates of the object in the coordinate system of the video frame displayed in the video display window 300.

And a play control 310, located at the upper right side of the video display window 300, for displaying the face image or the body image included in the alarm information.

Based on the graphical user interface, the video display method comprises the following steps.

Step 901, receiving externally input alarm information M displayed in a window list₁The selection instruction of (1).

In the embodiment of the application, a user can select the alarm information M associated with the target D from the plurality of alarm information displayed in the window list according to the information displayed on the graphical user interface₁Inputting the alarm information M to the server through the input device such as mouse and keyboard₁The selection instruction of (1).

In an alternative embodiment, alarm message M for selecting desired target D from window list is selected for user's convenience₁. The window list 320 may be specifically used to display a face image or a body image included in the alarm information. For example, as shown in fig. 7, in the left window list of the graphical user interface, a plurality of face images are displayed, and each face image corresponds to one piece of alarm information.

The process of displaying the face image or the body image in the window list 320 may include: the method comprises the steps that a server receives alarm information sent by a camera, wherein the alarm information comprises a corresponding relation between a global identification, track information and an image of a target; the server stores the alarm information, extracts the image of the target from the alarm information, displays the image of the target in the window list 320, and establishes the relationship between the image of the target and the global identifier in the alarm information.

Step 902, obtain alarm information M₁Track information M included₂Track information M₂Including at least one image coordinate of the object D.

The server acquires the alarm information M after receiving the selection instruction₁Track information M including an object D₂. Track information M₂Including at least one image coordinate of the object D.

In an alternative embodiment, the alarm information displayed on the window list 320 includes a human face image or a human body image, that is, the alarm information displayed on the window list 320 includes an image of the target. Based on this, the server receives a list of images T for display in the window list 320₁Upon receiving a selection instruction for the image T displayed in the window list 320₁After the selection instruction, determining the image T according to the corresponding relation between the pre-stored image and the global identification₁A corresponding first global identity. The server determines track information M corresponding to the first global identification according to the pre-stored corresponding relation between the global identification and the track information₂. Here, the pre-stored correspondence between the global identifier and the track information may be alarm information pre-stored by the server. The above alarm information may include a corresponding relationship between the global identifier and the track information and an image of the target.

And step 903, superposing at least one image coordinate on the video frame for display.

In an alternative embodiment, after acquiring the at least one image coordinate of the target D, the server may superimpose the at least one image coordinate on the video frame in the form of a point for display. As shown in fig. 10a, each solid dot in fig. 10a represents an image coordinate, and the trajectory information of the object D is composed of the plurality of image coordinates and is displayed superimposed on the video frame.

In another alternative embodiment, after acquiring the at least one image coordinate of the target D, the server may superimpose the at least one image coordinate on the video frame in a form of a link, as shown in fig. 10 b. Each solid dot in fig. 10c represents an image coordinate, and the plurality of image coordinates are connected by straight lines to constitute the trajectory information of the object D, which is displayed superimposed on the video frame.

In one example, for the convenience of viewing by the user, the server may select a target image coordinate meeting a preset condition from at least one image coordinate included in the alert information, superimpose the target image coordinate on a video frame for display, and connect the target image coordinates in a straight line. As shown in fig. 10 c. Each solid dot in fig. 10c represents an image coordinate. Determining target image coordinates from a plurality of image coordinates included in fig. 10b, connecting the plurality of target image coordinates by straight lines to form track information of the target D, and displaying the track information on the video frame in an overlapping manner.

The preset condition may be set according to a user requirement, for example, the preset condition may be that a distance between two image coordinates is greater than a distance threshold, or that a time interval for a target to reach the two image coordinates is greater than a time threshold. This is not limited in the embodiments of the present application.

In an alternative embodiment, in order to facilitate the user to observe the motion of the analysis target, the trajectory information may further include the elapsed time of each image coordinate of the target and the dwell time of the target at each image coordinate. The server acquires the track information M₂Then, each elapsed time and dwell time corresponding to the object D may be further superimposed on the corresponding image coordinates on the video frame for display, as shown in fig. 10 c.

In an alternative embodiment, after superimposing the at least one image coordinate on the video frame for display, the server may mark the object D at the latest image coordinate of the at least one image coordinate on the video frame. For example, the server may mark object D with a rectangular box, as shown in FIG. 7.

In an optional embodiment, in order to facilitate the user to observe the target, the target is associated with the track information of the target, and the server receives externally input alarm information M displayed in a window list₁After the selection instruction, the alarm information M can be acquired₁Including human face image or human body image, and displaying the obtained person on the playing controlFace images or body images. For example, as shown in fig. 7, the acquired face image is displayed in the play control 320.

Corresponding to the video display method embodiment, the embodiment of the application provides a video display device. Referring to fig. 11, fig. 11 is a schematic structural diagram of a video display device according to an embodiment of the present disclosure. The device is applied to a server with a graphical user interface, and the graphical user interface comprises:

a window list located on the right side of the graphical user interface for displaying the alarm information associated with each target sent by the camera; the alarm information associated with each target comprises track information of the target and an image containing the target, the track information of the target comprises at least one image coordinate of the target, and the image containing the target comprises a face image and/or a human body image of the target;

and the playing control is positioned at the upper right side of the video display window and used for displaying the human face image or the human body image included in the alarm information.

The video display device includes: a receiving module 1101, an obtaining module 1102 and a superimposing module 1103.

A receiving module 1101, configured to receive externally input alarm information M displayed in the window list₁A selection instruction of (1);

an obtaining module 1102, configured to obtain the alarm information M₁Track information M included₂Track information M₂At least one image coordinate comprising a target D;

and an overlaying module 1103, configured to overlay at least one image coordinate onto the video frame for display.

In an optional embodiment, the obtaining module 1102 may be further configured to receive externally input alarm information M displayed in a window list₁After the selection instruction, acquiring the alarm information M₁Including facial images or body images.

In this case, the video display device may further include: and the control module is used for controlling the playing control to display the acquired face image or the human body image.

In an optional embodiment, the window list may be specifically configured to display a face image or a human body image included in the alarm information.

In an alternative embodiment, the receiving module 1101 may be specifically configured to receive an externally input image T for display in a window list₁A selection instruction of (1);

the acquisition module 1102 may be specifically configured to determine the image T₁A first global identity of; determining track information M corresponding to the first global identification according to the corresponding relation between the global identification and the track information stored in advance₂。

In an alternative embodiment, the overlaying module 1103 may be specifically configured to overlay at least one image coordinate on the video frame in a dot or line form for display.

In an alternative embodiment, the track information M₂Also included is an elapsed time for the object D to pass each of the at least one image coordinate and a dwell time for the object D at each of the at least one image coordinate.

The superimposing module 1103 may be further configured to superimpose each elapsed time and the dwell time corresponding to the target D on the corresponding image coordinate of the video frame for display.

In an optional embodiment, the overlaying module 1103 may be further configured to mark the object D at the latest image coordinate of the at least one image coordinate on the video frame after the at least one image coordinate is overlaid on the video frame for display.

Corresponding to the above video display method embodiment, an embodiment of the present application further provides a server, as shown in fig. 12, including a processor 1201 and a memory 1202; a memory 1202 for storing a computer program; the processor 1201 is configured to implement any of the steps of the video display method described above when executing the computer program stored in the memory 1202. In the method, the server has a graphical user interface, and the graphical user interface includes:

the video display method comprises the following steps:

receiving externally input alarm information M aiming at display in window list₁A selection instruction of (1);

obtaining alarm information M₁Track information M included₂Track information M₂At least one image coordinate comprising a target D;

and at least one image coordinate is superposed on the video frame for display.

The Memory may include a RAM (Random Access Memory) or an NVM (Non-Volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.

The Processor may be a general-purpose Processor including a CPU (Central Processing Unit), an NP (Network Processor), and the like; but also DSPs (Digital Signal Processing), ASICs (Application Specific Integrated circuits), FPGAs (Field Programmable Gate arrays) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.

The embodiment of the application also provides a machine-readable storage medium, wherein a computer program is stored in the machine-readable storage medium, and when being executed by a processor, the computer program realizes any step of the video display method.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the embodiments of the video display apparatus, the server, and the machine-readable storage medium, since they are substantially similar to the embodiments of the video display method, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the embodiments of the video display method.

The above description is only for the preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. A video display method applied to a server having a graphical user interface, the graphical user interface comprising:

the video display window is positioned on the left side of the graphical user interface and is used for displaying video frames sent by the multiple sensor cameras in real time; the video frame comprises N targets, wherein N is a positive integer and is more than or equal to 1; the multi-sensor camera includes: the large-field-of-view lens assembly comprises a large-field-of-view lens assembly and a large-field-of-view sensor corresponding to the large-field-of-view lens assembly; at least one small-field-of-view lens component and a small-field-of-view sensor corresponding to the small-field-of-view lens component; the field angle of the large-field lens assembly is larger than that of the small-field lens assembly, and for the same target, the definition of the large-field sensor is smaller than that of the small-field sensor;

the processor of the multi-sensor camera is specifically configured to: performing human body analysis on a large-view-field video frame generated by the large-view-field sensor, and determining a first coordinate of a first target if the large-view-field video frame obtained through analysis comprises the first target; performing face analysis or head-shoulder analysis or human body analysis on the small view field video frame generated by the small view field sensor; if the small-view-field video frame obtained through analysis comprises a second target, detecting whether the second target leaves a view field range of a small-view-field lens assembly corresponding to the small-view-field video frame; when the second target is detected to leave the field range of the small-field lens assembly corresponding to the small-field video frame, generating track information aiming at the first target according to the recorded coordinates of the first target;

the method comprises the following steps:

2. Method according to claim 1, characterized in that the alarm information M displayed in the list of windows for receiving external input₁After the selecting instruction, the method further comprises:

acquiring the alarm information M₁Including face images or body images;

3. The method according to claim 1, wherein the window list is specifically used for displaying a face image or a human body image included in the alarm information.

4. Method according to claim 3, characterized in that said receiving of external input of alarm information M for display in said window list₁The step of selecting an instruction of (1), comprising:

determining the image T₁A first global identity of;

5. The method of claim 1, wherein said step of superimposing said at least one image coordinate onto said video frame for display comprises:

6. Method according to claim 1, characterized in that the trajectory information M₂Further comprising an elapsed time for the object D to pass each of the at least one image coordinate and a dwell time for the object D at each of the at least one image coordinate; the method further comprises the following steps:

7. The method of claim 1, further comprising, after displaying the at least one image coordinate superimposed on the video frame:

8. A video display apparatus, applied to a server having a graphical user interface, the graphical user interface comprising:

the device comprises:

9. A video display system, comprising a server having a graphical user interface, a plurality of sensor cameras connected to the server;

the processor of the multi-sensor camera is specifically configured to: performing human body analysis on the large-view-field video frame, and determining a first coordinate of a first target if the large-view-field video frame obtained through analysis comprises the first target; performing face analysis or head and shoulder analysis or human body analysis on the small view field video frame; if the small-view-field video frame obtained through analysis comprises a second target, detecting whether the second target leaves a view field range of a small-view-field lens assembly corresponding to the small-view-field video frame; when the second target is detected to leave the field range of the small-field lens assembly corresponding to the small-field video frame, generating track information aiming at the first target according to the recorded coordinates of the first target;

the graphical user interface includes:

10. The video display system of claim 9, wherein the processor of the multiple sensor camera is further configured to:

determining a first global identification of the first target;

11. The video display system of claim 10, wherein the processor of the multiple sensor camera is further configured to:

determining second coordinates of the second target;

12. The video display system of claim 11, wherein the processor of the multiple sensor camera is further configured to:

13. The video display system according to claim 11, wherein the step of detecting whether the distance between the second coordinate and the first coordinate is smaller than a first preset distance threshold to obtain a first detection result comprises:

14. A server, comprising a processor and a memory;

the memory is used for storing a computer program;

the processor, configured to execute the program stored in the memory, implements the method steps of any of claims 1-7.

15. A machine readable storage medium, characterized in that a computer program is stored in the machine readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of the claims 1-7.