CN117812392A - Resolution self-adaptive adjustment method, system, medium and device for visual screen - Google Patents
Resolution self-adaptive adjustment method, system, medium and device for visual screen Download PDFInfo
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Abstract
A resolution self-adaptive adjustment method, a system, a medium and equipment for a visual screen relate to the technical field of resolution adjustment. The method comprises the following steps: analyzing the current monitoring video to obtain a target traffic picture, and determining at least one associated picture associated with the target traffic picture and the display priority of each associated picture; determining a target resolution corresponding to the target traffic picture according to the target traffic picture and attribute information of the terminal equipment; matching corresponding target layout templates in a preset screen layout template library based on the number of the associated pictures, matching each associated picture to a display subarea corresponding to the target layout template based on the display priority of each associated picture, and matching the target traffic picture to a display center area to obtain a standard display picture; and performing visual display according to the resolution corresponding to each region in the standard display picture. By implementing the technical scheme provided by the application, the resolution can be adjusted in a self-adaptive manner, and the traffic management efficiency is improved.
Description
Technical Field
The application relates to the technical field of resolution adjustment, in particular to a resolution self-adaptive adjustment method, a system, a medium and equipment for a visual screen.
Background
In a smart city management center, a traffic monitoring system is a core component responsible for collecting, analyzing and presenting traffic flow data. These data are critical to both real-time traffic management and long-term city planning. Conventional traffic monitoring systems often rely on a set of fixed resolution cameras and sensors that transmit data in real time to a large screen of a central control room for display.
Large screens are key facilities for monitoring and responding to traffic conditions. The conventional large screen displays the display content according to the fixed resolution, however, in the period of traffic peak, the large screen cannot adjust the resolution of the displayed content according to the actual situation, which may cause the key information to be ignored, so that the manager is difficult to quickly and accurately receive the key traffic information, thereby affecting the efficiency of traffic management.
Disclosure of Invention
The resolution self-adaptive adjustment method, system, medium and equipment for the visual screen can adaptively adjust the resolution, so that a manager can quickly and accurately receive key traffic information, and the traffic management efficiency is improved.
In a first aspect, the present application provides a method for adaptively adjusting resolution of a visual screen, which is applied to a terminal device including the visual screen, and the method includes:
acquiring a current monitoring video of a target area, analyzing the current monitoring video to obtain a target traffic picture, determining at least one associated picture associated with the target traffic picture, and determining the display priority of each associated picture;
determining a target resolution corresponding to the target traffic picture according to the target traffic picture and attribute information of the terminal equipment;
matching corresponding target layout templates in a preset screen layout template library based on the number of the associated pictures, wherein the target local templates comprise at least one display center region and a plurality of display sub-regions, each display sub-region corresponds to a preset resolution, and each display center region corresponds to the target resolution;
based on the display priority of each associated picture, matching each associated picture to a display subarea corresponding to the target layout template, and matching the target traffic picture to a display center area to obtain a standard display picture;
And performing visual display according to the resolution corresponding to each region in the standard display picture.
By adopting the technical scheme, the target traffic picture is acquired by analyzing the monitoring video, and other auxiliary associated pictures associated with the target traffic picture are determined; then determining the target resolution of the display of the target traffic picture according to the content of the target traffic picture, matching the target layout template according to the number of the associated pictures, and placing the target traffic picture in a central high-resolution area and the associated pictures in surrounding sub-areas; finally, content display is carried out according to the preset resolution in the target layout template, compared with the traditional fixed resolution display, the method realizes the content self-adaptive adjustment of the traffic monitoring large screen, can dynamically adjust the resolution of the key area according to the importance degree of traffic conditions, highlights the key information, and improves the traffic management efficiency.
Optionally, the analyzing the current monitoring video to obtain a target traffic picture includes: analyzing the current monitoring video to obtain continuous frame pictures corresponding to a plurality of continuous video frames; preprocessing the continuous frame pictures to obtain standard continuous frame pictures; detecting the standard continuous frame pictures based on a deep learning model and a motion detection algorithm to obtain a detection result; and determining a target traffic picture based on the detection result.
By adopting the technical scheme, the continuous frame pictures obtained by analysis are preprocessed to obtain the standard continuous frame pictures, then the standard continuous frame pictures are subjected to target recognition and motion detection by using the deep learning model and the motion detection algorithm, and finally the target traffic picture is determined according to the detection result, so that the traffic picture with larger traffic flow and abnormal conditions such as accident congestion can be actively locked, and the detection efficiency of key traffic conditions is improved.
Optionally, the determining the target traffic picture based on the detection result includes: judging whether the standard continuous frame pictures in the detection result meet preset standard traffic rules or not; if the standard continuous frame images all accord with the preset standard traffic rules, determining that the current traffic condition is normal traffic, and taking the image corresponding to the preset area in the continuous frame images as a target traffic image; if the abnormal frames which do not accord with the preset standard traffic rules exist in the standard continuous frame frames, determining that the current traffic condition is abnormal traffic, and taking the abnormal frames as target traffic frames.
By adopting the technical scheme, judging whether the monitoring picture accords with the standard traffic rule, and if so, selecting a preset normal traffic area as a target picture; if the abnormal traffic picture is abnormal, the abnormal traffic picture which does not accord with the standard rule is taken as a target picture, so that intelligent judgment of traffic conditions and active locking of key pictures are realized. When abnormal conditions such as traffic accident congestion occur, the system can rapidly locate and enlarge and display the key areas, remind traffic managers of paying attention, and greatly improve the response speed to the abnormal conditions of traffic.
Optionally, the determining at least one associated picture associated with the target traffic picture and determining the presentation priority of each associated picture include: determining traffic key information in the target traffic picture; matching the traffic key information with a preset traffic database to obtain at least one associated key word associated with the target traffic picture, and obtaining an associated picture corresponding to each associated key word in the current monitoring video; calculating an association value between each associated keyword and the traffic key information, and determining the display priority of each associated picture based on each association value.
By adopting the technical scheme, the target traffic picture is automatically analyzed, the key information is extracted, and the key information is associated and matched with the preset traffic database to obtain the associated picture related to the target picture. And the association degree of each association picture can be calculated, the display priority of the association picture is automatically determined according to the association degree, the intelligentization of content understanding and association recommendation is realized, the road section monitoring related to key conditions such as traffic accident points can be actively acquired, and the traffic management personnel can be assisted in comprehensively mastering the conditions. Meanwhile, the relevance is automatically calculated, and relevant content with higher relevance is preferentially displayed, so that a person is helped to quickly focus on a key attention area.
Optionally, the attribute information includes a maximum resolution, and determining, according to the attribute information of the target traffic picture and the electronic device, the target resolution corresponding to the target traffic picture includes: determining an importance level of the target traffic picture based on the traffic key information; and determining the target resolution corresponding to the target traffic picture based on the importance level of the target traffic picture and the relation between the preset importance level and the resolution, wherein the target resolution is smaller than the maximum resolution.
By adopting the technical scheme, key information in the traffic picture is analyzed, the importance level is judged, and the proper target resolution is selected for display based on the corresponding relation between the preset importance level and the resolution. The target resolution can be controlled in a reasonable interval within the attribute range of the equipment, so that the content self-adaptive adjustment of the traffic picture is realized. For key traffic conditions, such as accident congestion points, the system can automatically improve the display resolution and highlight problem areas so as to remind traffic managers; for the secondary region, the system will properly reduce the resolution display, saving resources.
Optionally, the matching, based on the number of the associated frames, the corresponding target layout template in a preset screen layout template library includes: matching in a preset screen layout template library based on the number of the associated pictures to obtain at least one layout template corresponding to the number of the associated pictures; and determining a target local template in each layout template based on the hierarchy of the display priority of each associated picture.
By adopting the technical scheme, matching candidate layout templates are found in the template library according to the number of the associated pictures; and then, according to the priority of each associated picture, evaluating and determining an optimal layout scheme in the candidate templates as a display template, so that intelligent optimization of large-screen layout is realized, screen layout is automatically organized, the definition and efficiency of visual information transmission are greatly improved, and traffic managers are helped to quickly locate focus of attention.
Optionally, the visually displaying according to the resolution corresponding to each area in the standard display picture includes: if the current traffic condition is normal traffic, adjusting the resolution corresponding to each region in the standard display picture to be a preset low resolution, and performing visual display according to the preset low resolution; and if the current traffic condition is abnormal traffic, visually displaying according to the resolution corresponding to each region in the standard display picture.
By adopting the technical scheme, the resolution of the display of the monitoring picture can be intelligently adjusted according to the normal or abnormal condition of the traffic condition. When the traffic is normal, the visual presentation is performed by using a preset low resolution so as to save system resources; and when the traffic is abnormal, the visual presentation is performed according to the matched high resolution so as to emphasize the key condition.
In a second aspect of the present application there is provided a resolution adaptive adjustment system for a visual screen, the system comprising:
the video analyzing module is used for acquiring a current monitoring video of a target area, analyzing the current monitoring video to obtain a target traffic picture, determining at least one associated picture associated with the target traffic picture, and determining the display priority of each associated picture;
the resolution determining module is used for determining a target resolution corresponding to the target traffic picture according to the target traffic picture and the attribute information of the terminal equipment;
the layout matching module is used for matching corresponding target layout templates in a preset screen layout template library based on the number of the associated pictures, the target local template comprises at least one display center area and a plurality of display subareas, each display subarea corresponds to a preset resolution, and the display center area corresponds to the target resolution
The display picture determining module is used for matching each associated picture to a display subarea corresponding to the target layout template based on the display priority of each associated picture, and matching the target traffic picture to a display center area to obtain a standard display picture;
And the visual display module is used for performing visual display according to the resolution corresponding to each region in the standard display picture.
In a third aspect the present application provides a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.
In a fourth aspect of the present application, there is provided an electronic device comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. the method comprises the steps of obtaining a target traffic picture through analyzing a monitoring video, and determining other auxiliary associated pictures associated with the target traffic picture; then determining the target resolution of the display of the target traffic picture according to the content of the target traffic picture, matching the target layout template according to the number of the associated pictures, and placing the target traffic picture in a central high-resolution area and the associated pictures in surrounding sub-areas; finally, content display is carried out according to the preset resolution in the target layout template, compared with the traditional fixed resolution display, the method realizes the content self-adaptive adjustment of the traffic monitoring large screen, can dynamically adjust the resolution of the key area according to the importance degree of traffic conditions, highlights the key information, and improves the traffic management efficiency;
2. According to the method, the continuous frame pictures obtained through analysis are preprocessed to obtain standard continuous frame pictures, then the standard continuous frame pictures are subjected to target recognition and motion detection by using a deep learning model and a motion detection algorithm, and finally the target traffic picture is determined according to the detection result, so that traffic pictures with larger traffic flow and abnormal conditions such as accident congestion can be actively locked, and the detection efficiency of key traffic conditions is improved;
3. judging whether the monitoring picture accords with the standard traffic rule or not, and if so, selecting a preset normal traffic area as a target picture; if the abnormal traffic picture is abnormal, the abnormal traffic picture which does not accord with the standard rule is taken as a target picture, so that intelligent judgment of traffic conditions and active locking of key pictures are realized. When abnormal conditions such as traffic accident congestion occur, the system can rapidly locate and enlarge and display the key areas, remind traffic managers of paying attention, and greatly improve the response speed to the abnormal conditions of traffic.
Drawings
Fig. 1 is a schematic flow chart of a method for adaptively adjusting resolution of a visual screen according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a resolution adaptive adjustment system for a visual screen according to an embodiment of the present application;
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 300. an electronic device; 301. a processor; 302. a communication bus; 303. a user interface; 304. a network interface; 305. a memory.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.
In the description of embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described herein as "such as" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of the embodiments of the present application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
The following description of the embodiments of the present application will be given in detail with reference to the accompanying drawings, and it is apparent that the embodiments described are only some, but not all embodiments of the present application.
Referring to fig. 1, a flow chart of a method for adaptively adjusting resolution of a visual screen is specifically provided, the method may be implemented by a computer program, may be implemented by a single chip microcomputer, may also be run on a system for adaptively adjusting resolution of a visual screen, the computer program may be integrated in a terminal device of the visual screen, and may also be run as an independent tool application, and specifically, the method includes steps 10 to 50, where the steps are as follows:
step 10: the method comprises the steps of obtaining a current monitoring video of a target area, analyzing the current monitoring video to obtain a target traffic picture, determining at least one associated picture associated with the target traffic picture, and determining the display priority of each associated picture.
Specifically, the target area refers to a specific geographical area or road segment, such as a section of a critical intersection, bridge or highway, where traffic monitoring is required. In order to realize intelligent monitoring and analysis of traffic conditions, a real-time monitoring video containing a target area needs to be acquired, and the video content is analyzed, so that a key traffic picture is acquired. The real-time video stream of the target area can be obtained from the preset traffic monitoring camera, the video frame is analyzed by utilizing an image processing technology, and the target traffic picture containing traffic jam conditions is identified through the deep learning model. Then, other auxiliary association pictures related to the target traffic picture need to be determined so that the traffic manager can fully observe the event development. The content analysis can be performed on the target picture, and key information of traffic jam, such as places, road names and the like, can be extracted. And matching the traffic information with a background traffic database, and acquiring the monitoring of the related road sections around the accident point as the related pictures. And calculating the semantic association degree of each associated picture, and determining the display priority for each associated picture according to the association degree from high to low. Therefore, when a traffic manager looks at a large screen, the traffic manager can pay attention to the road section more relevant to the accident point first, and assist in making decisions quickly.
On the basis of the above embodiment, as an optional embodiment, the step of analyzing the current monitoring video to obtain the target traffic picture may further include the steps of:
step 101: analyzing the current monitoring video to obtain continuous frame pictures corresponding to a plurality of continuous video frames.
Specifically, in order to extract continuous traffic pictures from the current monitoring video, the monitoring video needs to be analyzed to obtain a plurality of video frames, the acquired traffic monitoring video is subjected to frame sequence decomposition, and continuous frame pictures in time sequence are extracted. The video data stream may be broken up into individual frames according to the time stamp information in the video encoding format and organized into a time-ordered frame queue. For each frame, the time point of occurrence is recorded, and a logical connection relationship is formed with the adjacent preceding and following frames. The result of such parsing is a set of consecutive frames that preserve time-course information of object motion and traffic flow changes in the video.
Step 102: and preprocessing the continuous frame pictures to obtain standard continuous frame pictures.
In order to improve the recognition effect of the follow-up algorithm on the traffic picture, the extracted original continuous frame picture needs to be preprocessed, and a standardized picture is output. Specifically, denoising is performed on the collected original continuous frame images so as to filter the influence of car light rays and camera noise on the image quality. And then, parameters such as picture color, contrast and the like are adjusted, so that the picture color tone and effect acquired by different cameras in different time periods are unified. Then adjusting the picture size, cutting to key areas, and eliminating irrelevant background interference. The preprocessed standard continuous frame pictures can eliminate the difference caused by the change of the acquisition conditions, improve the prominence of key traffic objects, and are beneficial to the algorithm extraction of the key information such as traffic flow, vehicles and the like. And the calculation amount of subsequent analysis can be reduced, and the processing efficiency is improved.
Step 103: and detecting the standard continuous frame pictures based on the deep learning model and the motion detection algorithm to obtain a detection result.
Step 104: and determining a target traffic picture based on the detection result.
Specifically, a trained convolutional neural network is used for carrying out target recognition on each frame of picture, and traffic objects such as vehicles and crowds in the picture and information such as quantity and speed of the traffic objects are detected. Meanwhile, the motion track algorithm is used for analyzing the motion change of the object between two frames of images and judging the traffic flow speed and the traffic state. The semantic analysis capability of the deep learning algorithm and the dynamic analysis advantage of motion detection are comprehensively utilized, so that the traffic flow parameters in the picture can be accurately obtained, and the traffic conditions such as normal traffic, traffic jams, traffic accidents and the like can be intelligently judged. And outputting composite detection results including target identification results, flow statistics data, traffic state judgment and the like by a final algorithm. And analyzing the detection result of each group of standard continuous frame pictures, and judging traffic event information such as traffic flow, congestion state, accident abnormal condition and the like in the pictures. According to a preset key event judging rule, if the detection result shows normal flow distribution, the system selects a fixed key intersection picture with the largest visual angle range as a target traffic picture; if an accident or congestion event is detected, a picture containing a target event occurrence point is determined as a target traffic picture.
On the basis of the above embodiment, as an optional embodiment, the step of determining the target traffic picture based on the detection result may further include the steps of:
step 1041: and judging whether the standard continuous frame pictures in the detection result all accord with the preset standard traffic rules.
Step 1042: if the standard continuous frame pictures all accord with the preset standard traffic rules, determining that the current traffic condition is normal traffic, and taking the picture corresponding to the preset area in the continuous frame picture as the target traffic picture.
Step 1043: if the abnormal frames which do not accord with the preset standard traffic rules exist in the standard continuous frame frames, determining that the current traffic condition is abnormal traffic, and taking the abnormal frames as target traffic frames.
Specifically, the traffic parameter detection result of the standard continuous frame pictures is judged, and whether the standard continuous frame pictures in the detection result meet the preset standard traffic rules is judged. The preset standard traffic rule refers to a set of quantization parameter index systems defining normal traffic conditions, such as preset traffic flow, speed range and the like, to determine whether the normal traffic conditions are met. If the detection results of the standard continuous frame pictures are all in the normal range, judging that the road section is normal traffic currently, and automatically selecting a preset key node picture of the road section as a monitoring target. If the detection result of some frame pictures exceeds the abnormal conditions such as the congestion flow threshold value, the vehicle stagnation and the like, judging that the traffic is abnormal or accident, and taking the frame picture containing abnormal information as a target traffic picture.
Illustratively, it is assumed that traffic conditions at an expressway exit toll station need to be monitored. The system acquires the monitoring video of the toll station for 24 hours, and analyzes and extracts the sequential video frame pictures. For each group of consecutive frames, the system detects parameters such as the number of vehicles, the speed of movement, etc. in each frame using a deep learning algorithm. Judging according to a preset standard traffic rule of the road section: the rules prescribe that the normal traffic flow is 60-100 vehicles per minute, the vehicle speed is 60-100 km/h, and if the duration exceeds 5 minutes, the congestion is judged. If the detection results of all frames are in a normal range, such as the early and late peak time, the traffic flow of each frame is about 80, and the vehicle speed is 80 km, the system judges that the traffic state is normal. Thus, the system can automatically select the panoramic view angle picture preset by the toll station as a monitoring target picture. If the detection result of some frames is abnormal, for example, in the early morning time period, the single-frame traffic flow is reduced to about 10 vehicles and the vehicle speed is 20 km, the system can judge the abnormal traffic state, and the pictures containing the abnormal frames are selected as key target pictures to prompt the attention of the operator on duty.
On the basis of the above embodiment, as an optional embodiment, determining at least one associated screen associated with the target traffic screen, and determining a presentation priority of each associated screen may further include the steps of:
In particular, to assist traffic administrators in more fully assessing and handling traffic events, the system needs to actively acquire monitoring pictures of other auxiliary perspectives related to key target pictures. And analyzing the target traffic picture by using a computer vision algorithm, and extracting traffic key information in the target traffic picture, such as vehicles, crowd distribution, road conditions and the like, so as to help the system to understand picture content and event points in depth. And inquiring related keywords corresponding to the key information, such as terms of traffic accidents, traffic jams, construction and the like, in a preset traffic keyword database, wherein the related keywords are used as high-level semantic description of the event, and the high-level semantic description is a conversion process from low-level visual information to high-level concepts. And searching the monitoring video stream globally, searching out a real-time picture containing the associated keywords, and acquiring associated pictures under other view angles with semantic association with the target event. And calculating the relevance of each keyword and the traffic event as a weight, evaluating the semantic relevance of the pictures, sequencing the related pictures according to the weight, and determining the display priority.
Illustratively, it is assumed that the system determines an abnormal target traffic picture including a traffic accident from the highway monitoring video. To coordinate the traffic manager's handling of events, the system needs to acquire additional auxiliary perspectives associated with this target view. And analyzing the target traffic picture, and extracting traffic key information such as an automobile, a warning lamp, a collapse guardrail and the like by using a target detection algorithm. And inquiring entries related to the key information, such as 'accident scene', 'emergency lane', 'traffic jam', and the like, in a background preset traffic key word database as related key words, and extracting real-time pictures containing the related key words from the current monitoring video of the expressway. Such as a monitor screen upstream in one direction, a monitor screen downstream in the opposite direction, and the like. And calculating the correlation degree of each associated keyword and the accident, for example, the highest correlation degree of the accident scene and the emergency lane are inferior. And determining the display priority for the associated pictures, and focusing on the pictures with higher keyword relevance. Through key information analysis and database matching, other supplementary view angles closely related to the emergency are actively obtained, and the multi-dimensional comprehensive monitoring of traffic conditions is realized.
Step 20: and determining the target resolution corresponding to the target traffic picture according to the target traffic picture and the attribute information of the terminal equipment.
Specifically, firstly, the content characteristics of the target traffic picture are analyzed, and the number of key monitoring objects, the moving speed, the scene complexity and the like contained in the picture are judged, so that an ideal resolution range of the display picture is determined. It is also necessary to determine the hardware parameters of the terminal device, such as the screen size, the maximum supported resolution, etc., which determine the upper resolution limit at which the picture is presented. Comprehensively considering the resolution requirement of the picture content and the condition constraint of the terminal equipment, and determining the optimal target output resolution for the key monitoring content under the current equipment condition by using a multi-attribute decision method. The target traffic picture can achieve the best visual effect on different user equipment. The system is assumed to judge a key target traffic picture containing traffic accident scene from the expressway monitoring video. The system is a 1920x1080 resolution high definition video picture, and by inquiring the database, the system knows that the terminal equipment used by the traffic manager at the moment is a medium and small monitoring screen with the maximum resolution of 1280x720, and in order to achieve the best monitoring effect on the equipment screen, the system needs to calculate the matched target output resolution, for example, the key detail information contained in the target picture, such as the vehicle photo definition requirement of the accident scene, the resolution and the size attribute of the terminal equipment screen, the historical operation habit of the user, such as preference of a wide screen picture, and the like, can be considered. After comprehensively considering the factors, the system calculates and determines that the optimal target resolution is 1280x720, so that key details can be clearly displayed on a screen, and the hardware conditions of the terminal equipment are matched.
On the basis of the above embodiment, as an optional embodiment, the step of determining, according to the visibility, the target resolution corresponding to the target traffic picture and the attribute information of the terminal device, may further include the steps of:
step 201: the importance level of the target traffic picture is determined based on the traffic key information.
Step 202: and determining the target resolution corresponding to the target traffic picture based on the importance level of the target traffic picture and the relation between the preset importance level and the resolution, wherein the target resolution is smaller than the maximum resolution.
Specifically, a computer vision algorithm may be invoked to analyze and extract traffic key information of the target traffic picture, such as the number of vehicles, speed, whether accident features are included, and the like. According to the key information, the system matches preset corresponding rules of the key information and the importance level, and calculates and determines the comprehensive importance level of the current target picture. For example, the accident picture has the highest importance level, the high-speed congestion is secondary, and the normal road condition has the lowest importance level. Determining a target resolution corresponding to the target traffic picture based on an importance level of the target traffic picture and a relationship between a preset importance level and a preset resolution, wherein the relationship between the preset importance level and the preset resolution refers to a mapping relationship table or model between an importance level and a corresponding resolution value, and the importance level can be defined in multiple stages, for example: importance level 1: normal road conditions, importance level 2: mild congestion, importance level 3: severe congestion and importance level 4: accident scene. There may also be a number of alternatives to the resolution value, for example: 720P, 1080P, 2K, 4K, etc. then establishes a mapping relationship, such as: importance levels 1>720P, importance levels 2>1080P, importance levels 3>2K, importance levels 4>4K, etc., and the relationship between the importance levels and the resolution can be adjusted according to the actual situation and usual visual habits of the user.
Step 30: the method comprises the steps that based on the number of associated pictures, corresponding target layout templates are matched in a preset screen layout template library, a target local template comprises at least one display center area and a plurality of display subareas, each display subarea corresponds to preset resolution, and the display center area corresponds to target resolution.
Specifically, the total number of associated frames required to be displayed simultaneously is counted, the associated frames are obtained from keyword matching results, matching is performed in a preset screen layout template library, at least one layout template corresponding to the number of the associated frames is obtained, each layout template comprises at least one display center area and a plurality of display subareas, for example, 3 associated frames match a plurality of layout templates comprising 3 display subareas, for example, the layout templates with subareas of three equal sizes may be used, and the layout templates with subareas of different sizes may be used. And acquiring the hierarchy of the display priority of each associated picture, wherein the hierarchy of the display priority refers to the result of the priority ordering of each associated picture, for example, the situation that the priority is the same or the priority is gradually increased exists, and determining the target local template in each layout template according to the hierarchy of the display priority of each associated picture. Each display subarea corresponds to a preset resolution, and the display center area corresponds to the target resolution calculated in the previous step. Assuming that the associated pictures to be displayed currently have A, B, C, D four, the display priority levels of the associated pictures are arranged in a hierarchy of A=C > B=D, wherein A and C have equal priority levels, B and D have equal priority levels, and B and D have lower priority levels, so that the layout of the target local template which is matched finally is one display center area and four display subareas, wherein two subareas with different sizes exist in the four display subareas, and each subarea with different sizes exists in the four display subareas.
Step 40: and matching each associated picture to a display subarea corresponding to the target layout template based on the display priority of each associated picture, and matching the target traffic picture to a display center area to obtain a standard display picture.
Specifically, the layout style of the target layout template is analyzed, wherein the target layout template comprises a display center area and a plurality of display subareas, and the areas are respectively provided with a priority level. And matching the target traffic picture with the highest priority with the display center area, and sequentially matching the target traffic picture with each sub-display according to the display priority of each associated picture, so that pictures with different priorities are matched to the proper display area in the target layout template, and a standard display picture with clear information hierarchy and optimized monitoring resource utilization is formed.
Step 50: and performing visual display according to the resolution corresponding to each region in the standard display picture.
Specifically, after the standard display picture is generated, judging whether the current traffic condition belongs to a normal condition or an abnormal condition, if the current traffic condition is the normal traffic condition, considering that the traffic flow is normal and smooth, uniformly adjusting the resolution of each area in the standard display picture to be a preset low resolution such as 720P, processing the associated pictures in all areas according to the low resolution, and performing visual integrated display. If the abnormal traffic condition is judged, and key details need to be checked, the original resolution of each area in the standard display picture is maintained, specifically, the resolution parameter corresponding to each area in the target layout template is obtained, wherein the display center area corresponds to the target resolution of the target traffic picture obtained by the previous calculation, and each display subarea also has the preset default display resolution. Traversing all relevant pictures in the standard display pictures in sequence, carrying out necessary resolution adjustment on the pictures in each area according to the parameter requirements of each display resolution in the target layout template, and completing downsampling or upsampling operation of the pictures through an image processing algorithm. And combining and rendering all the associated pictures and the target traffic pictures after the resolution is adjusted into the corresponding areas of the standard display pictures, so that the integrated visual display of the complete standard display pictures is realized, and an optimized traffic monitoring result is provided for a user.
Referring to fig. 2, a schematic diagram of a resolution adaptive adjustment system for a visual screen according to an embodiment of the present application is provided, where the resolution adaptive adjustment system for a visual screen may include: the system comprises a video analysis module, a resolution determination module, a layout matching module, a display picture determination module and a visual display module, wherein:
the video analyzing module is used for acquiring a current monitoring video of a target area, analyzing the current monitoring video to obtain a target traffic picture, determining at least one associated picture associated with the target traffic picture, and determining the display priority of each associated picture;
the resolution determining module is used for determining a target resolution corresponding to the target traffic picture according to the target traffic picture and the attribute information of the terminal equipment;
the layout matching module is used for matching corresponding target layout templates in a preset screen layout template library based on the number of the associated pictures, the target local template comprises at least one display center area and a plurality of display subareas, each display subarea corresponds to a preset resolution, and the display center area corresponds to the target resolution
The display picture determining module is used for matching each associated picture to a display subarea corresponding to the target layout template based on the display priority of each associated picture, and matching the target traffic picture to a display center area to obtain a standard display picture;
and the visual display module is used for performing visual display according to the resolution corresponding to each region in the standard display picture.
Optionally, the video parsing module is further configured to parse the current monitoring video to obtain continuous frame frames corresponding to a plurality of continuous video frames; preprocessing the continuous frame pictures to obtain standard continuous frame pictures; detecting the standard continuous frame pictures based on a deep learning model and a motion detection algorithm to obtain a detection result; and determining a target traffic picture based on the detection result.
Optionally, the video analysis module is further configured to determine whether the standard continuous frame images in the detection result all conform to a preset standard traffic rule; if the standard continuous frame images all accord with the preset standard traffic rules, determining that the current traffic condition is normal traffic, and taking the image corresponding to the preset area in the continuous frame images as a target traffic image; if the abnormal frames which do not accord with the preset standard traffic rules exist in the standard continuous frame frames, determining that the current traffic condition is abnormal traffic, and taking the abnormal frames as target traffic frames.
Optionally, the video parsing module is further configured to determine traffic key information in the target traffic picture; matching the traffic key information with a preset traffic database to obtain at least one associated key word associated with the target traffic picture, and obtaining an associated picture corresponding to each associated key word in the current monitoring video; calculating an association value between each associated keyword and the traffic key information, and determining the display priority of each associated picture based on each association value.
Optionally, the resolution determining module is further configured to determine an importance level of the target traffic picture based on the traffic key information; and determining the target resolution corresponding to the target traffic picture based on the importance level of the target traffic picture and the relation between the preset importance level and the resolution, wherein the target resolution is smaller than the maximum resolution.
Optionally, the layout matching module is further configured to match in a preset screen layout template library based on the number of the associated frames, to obtain at least one layout template corresponding to the number of the associated frames; and determining a target local template in each layout template based on the hierarchy of the display priority of each associated picture.
Optionally, the visual display module is further configured to adjust the resolution corresponding to each area in the standard display screen to a preset low resolution if the current traffic situation is normal traffic, and perform visual display according to the preset low resolution; and if the current traffic condition is abnormal traffic, visually displaying according to the resolution corresponding to each region in the standard display picture.
It should be noted that: in the system provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the system and method embodiments provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the system and method embodiments are detailed in the method embodiments, which are not repeated herein.
The embodiment of the present application further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, where the instructions are suitable for being loaded by a processor and executed by a processor, and a specific execution process may refer to a specific description of the foregoing embodiment, and is not repeated herein.
Please refer to fig. 3, the present application also discloses an electronic device. Fig. 3 is a schematic structural diagram of an electronic device according to the disclosure in an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, at least one communication bus 302.
Wherein the communication bus 302 is used to enable connected communication between these components.
The user interface 303 may include a Display screen (Display), a Camera (Camera), and the optional user interface 303 may further include a standard wired interface, and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and invoking data stored in the memory 305. Alternatively, the processor 301 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 301 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 301 and may be implemented by a single chip.
The Memory 305 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 305 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. Memory 305 may also optionally be at least one storage device located remotely from the aforementioned processor 301. Referring to fig. 3, an operating system, a network communication module, a user interface module, and an application program of a resolution adaptive adjustment method of a visual screen may be included in the memory 305 as a computer storage medium.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 301 may be used to invoke an application program in the memory 305 that stores a method for adaptive adjustment of resolution of a visual screen, which when executed by the one or more processors 301, causes the electronic device 300 to perform the method as described in one or more of the embodiments above. It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.
This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.
Claims (10)
1. A method for adaptively adjusting resolution of a visual screen, which is applied to a terminal device including the visual screen, the method comprising:
acquiring a current monitoring video of a target area, analyzing the current monitoring video to obtain a target traffic picture, determining at least one associated picture associated with the target traffic picture, and determining the display priority of each associated picture;
determining a target resolution corresponding to the target traffic picture according to the target traffic picture and attribute information of the terminal equipment;
matching corresponding target layout templates in a preset screen layout template library based on the number of the associated pictures, wherein the target local templates comprise at least one display center region and a plurality of display sub-regions, each display sub-region corresponds to a preset resolution, and each display center region corresponds to the target resolution;
Based on the display priority of each associated picture, matching each associated picture to a display subarea corresponding to the target layout template, and matching the target traffic picture to a display center area to obtain a standard display picture;
and performing visual display according to the resolution corresponding to each region in the standard display picture.
2. The method for adaptively adjusting the resolution of a visual screen according to claim 1, wherein the analyzing the current surveillance video to obtain the target traffic picture comprises:
analyzing the current monitoring video to obtain continuous frame pictures corresponding to a plurality of continuous video frames;
preprocessing the continuous frame pictures to obtain standard continuous frame pictures;
detecting the standard continuous frame pictures based on a deep learning model and a motion detection algorithm to obtain a detection result;
and determining a target traffic picture based on the detection result.
3. The method for adaptively adjusting the resolution of a visual screen according to claim 2, wherein the determining a target traffic picture based on the detection result comprises:
judging whether the standard continuous frame pictures in the detection result meet preset standard traffic rules or not;
If the standard continuous frame images all accord with the preset standard traffic rules, determining that the current traffic condition is normal traffic, and taking the image corresponding to the preset area in the continuous frame images as a target traffic image;
if the abnormal frames which do not accord with the preset standard traffic rules exist in the standard continuous frame frames, determining that the current traffic condition is abnormal traffic, and taking the abnormal frames as target traffic frames.
4. The method of claim 1, wherein the determining at least one associated frame associated with the target traffic frame and determining a presentation priority for each of the associated frames comprises:
determining traffic key information in the target traffic picture;
matching the traffic key information with a preset traffic database to obtain at least one associated key word associated with the target traffic picture,
acquiring associated pictures corresponding to the associated keywords from the current monitoring video;
calculating an association value between each associated keyword and the traffic key information, and determining the display priority of each associated picture based on each association value.
5. The method for adaptively adjusting the resolution of a visual screen according to claim 4, wherein the attribute information includes a maximum resolution, and the determining the target resolution corresponding to the target traffic picture according to the target traffic picture and the attribute information of the electronic device includes:
determining an importance level of the target traffic picture based on the traffic key information;
and determining the target resolution corresponding to the target traffic picture based on the importance level of the target traffic picture and the relation between the preset importance level and the resolution, wherein the target resolution is smaller than the maximum resolution.
6. The method for adaptively adjusting resolution of a visual screen according to claim 4, wherein said matching a corresponding target layout template in a preset screen layout template library based on the number of associated pictures comprises:
matching in a preset screen layout template library based on the number of the associated pictures to obtain at least one layout template corresponding to the number of the associated pictures;
and determining a target local template in each layout template based on the hierarchy of the display priority of each associated picture.
7. The method for adaptively adjusting the resolution of a visual screen according to claim 3, wherein the performing visual display according to the resolution corresponding to each region in the standard display picture comprises:
if the current traffic condition is normal traffic, adjusting the resolution corresponding to each region in the standard display picture to be a preset low resolution, and performing visual display according to the preset low resolution;
and if the current traffic condition is abnormal traffic, visually displaying according to the resolution corresponding to each region in the standard display picture.
8. A resolution adaptive adjustment system for a visualization screen, the system comprising:
the video analyzing module is used for acquiring a current monitoring video of a target area, analyzing the current monitoring video to obtain a target traffic picture, determining at least one associated picture associated with the target traffic picture, and determining the display priority of each associated picture;
the resolution determining module is used for determining a target resolution corresponding to the target traffic picture according to the target traffic picture and the attribute information of the terminal equipment;
The layout matching module is used for matching corresponding target layout templates in a preset screen layout template library based on the number of the associated pictures, the target local template comprises at least one display center area and a plurality of display subareas, each display subarea corresponds to a preset resolution, and the display center area corresponds to the target resolution
The display picture determining module is used for matching each associated picture to a display subarea corresponding to the target layout template based on the display priority of each associated picture, and matching the target traffic picture to a display center area to obtain a standard display picture;
and the visual display module is used for performing visual display according to the resolution corresponding to each region in the standard display picture.
9. A computer readable storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the method of any one of claims 1 to 7.
10. An electronic device comprising a processor, a memory, a user interface, and a network interface, the memory for storing instructions, the user interface and the network interface for communicating to other devices, the processor for executing the instructions stored in the memory to cause the electronic device to perform the method of any of claims 1-7.
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