CN116156253B - Visualization method for video monitoring on intelligent large screen - Google Patents
Visualization method for video monitoring on intelligent large screen Download PDFInfo
- Publication number
- CN116156253B CN116156253B CN202310049956.XA CN202310049956A CN116156253B CN 116156253 B CN116156253 B CN 116156253B CN 202310049956 A CN202310049956 A CN 202310049956A CN 116156253 B CN116156253 B CN 116156253B
- Authority
- CN
- China
- Prior art keywords
- video
- threshold value
- threshold
- time
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 15
- 238000007794 visualization technique Methods 0.000 title claims description 3
- 238000000034 method Methods 0.000 claims abstract description 17
- 230000000903 blocking effect Effects 0.000 claims abstract description 5
- 230000008569 process Effects 0.000 claims abstract description 5
- 230000004048 modification Effects 0.000 claims description 4
- 238000012986 modification Methods 0.000 claims description 4
- 230000002159 abnormal effect Effects 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000000007 visual effect Effects 0.000 abstract description 3
- 230000000694 effects Effects 0.000 abstract description 2
- 238000012545 processing Methods 0.000 description 3
- 238000012800 visualization Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
Abstract
The invention provides a visual method for a video monitoring intelligent large screen, and belongs to the technical field of video monitoring. And reasonably improving or reducing the quality of each video picture according to the resource availability condition of the intelligent large screen in the current running state and the resource occupancy rate of all picture configuration. In the video playing process, the resource availability condition of the intelligent large screen and the operation fluency condition of the user are monitored in real time, the quality of partial video pictures is dynamically changed, the system resources are utilized to the greatest extent, clear fluency of the pictures is ensured, no blocking or frame loss is caused in operation, and the best experience of the user on the display effect is provided.
Description
Technical Field
The invention relates to a visual method of a video monitoring intelligent large screen, and belongs to the technical field of video monitoring.
Background
Visualization (Visualization) is a theory, method and technique for converting data into graphics or images to be displayed on a screen using computer graphics and image processing techniques, and then performing interactive processing.
At present, a picture segmentation mode is commonly used in the video monitoring industry. Several pictures are compressed on the same scale on the screen of a monitor by adopting the methods of image compression and digital processing. And the function of a built-in sequence switcher is also provided, and the function can output and display full-screen pictures input by each camera on a monitor in turn according to sequence and interval time.
However, due to various types of intelligent equipment, the performance difference is very large, and along with the high definition of the video industry, if the system resources cannot be reasonably utilized according to the current equipment, equipment is blocked, normal operation cannot be realized, and the user experience is very poor.
Disclosure of Invention
The invention aims to provide a visual method for video monitoring on an intelligent large screen, which can smoothly play all video pictures without influencing user operation and greatly improves user experience.
The invention aims to achieve the aim, and the aim is achieved by the following technical scheme:
Step 1: receiving video configuration of a background, monitoring the utilization condition of system resources by loading videos with different resolutions and different code stream types, and recording the utilization condition of the system resources; the system resource use condition is the system CPU occupancy rate;
step 2: after the video is loaded successfully and played normally, calculating system resources consumed by loading the current video configuration according to the current CPU occupancy rate minus the CPU occupancy rate of the unloaded video; continuously loading 2-4 videos, calculating the average consumption system resource condition of each video, and calculating the system resource required by loading the video pictures configured in the background by multiplying the average consumption system resource condition of each video by the number of the video pictures configured in the background;
step 3: judging the sizes of system idle resources and system resources required by background configuration, if the system idle resources are larger than the system resources required by the background configuration, maintaining the current image quality, and if the system idle resources are smaller than the system resources required by the background configuration, reducing the video image quality;
step 4: judging the system resource occupancy rate after loading all video pictures and the magnitudes of a first threshold value and a second threshold value;
If the video quality is greater than the threshold value I, reducing part of video picture quality until the video quality is lower than the threshold value I, wherein the initial value of the threshold value I is set to be 70%;
If the video picture quality is smaller than the threshold value II, the video picture quality is improved until the video picture quality rises to be higher than the threshold value II and lower than the threshold value I, and the initial value of the threshold value II is set to be 40%;
step 5: monitoring user operation and program response time in real time, judging whether the user operation is abnormal or not, and determining the current page clamping condition;
Step 6: and modifying the values of the first threshold value and the second threshold value according to whether the page is blocked or not until the most reasonable threshold value and the configuration of all video pictures are calculated, and outputting and displaying.
Preferably, the CPU occupancy rate calculating method is as follows: CPU occupancy= ((appCPUTime 2-appCPUTime 1)/(totalCPUTime 2-toalCPUTime) x 100, appcputime1 indicates the time when the current App process uses the CPU at any moment, appCPUTime2 indicates the time when the App process uses the CPU at any moment, totalCPUTime1 indicates the time when the current system uses the CPU at any moment, and totalCPUTime2 indicates the time when the system uses the CPU at any moment.
Preferably, the specific steps in the step 5 are as follows: when a video frame takes much more than 16ms, the following two conditions are satisfied at the same time: and the current frame time consumption is 2 times of the average time consumption of the first three frames, and the current frame time consumption is 2 times of the time consumption of the two frames of video frames, and the current frame time consumption is judged to be the stuck time.
Preferably, the way to modify the first threshold value and the second threshold value in the step 6 is as follows: when the page is blocked, the threshold I and the threshold II are reduced by 5% at the same time, if the threshold I and the threshold II are reduced, the video picture is smoothly played, and the user operation is free of blocking.
The invention has the advantages that: the method and the system monitor the resource availability condition of the intelligent large screen and the operation fluency condition of the user in real time, dynamically change the quality of partial video pictures, maximally utilize system resources, ensure clear and fluent pictures, avoid blocking operation and frame loss, and provide the user with the best experience on the display effect.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Step 1: receiving video configuration of a background, monitoring the utilization condition of system resources by loading videos with different resolutions and different code stream types, and recording the utilization condition of the system resources; the system resource use condition is the system CPU occupancy rate;
The CPU occupancy rate calculation mode is as follows: CPU occupancy= ((appCPUTime 2-appCPUTime 1)/(totalCPUTime 2-toalCPUTime 1)) 100
Step 2: after the video is loaded successfully and played normally, calculating system resources consumed by loading the current video configuration according to the current CPU occupancy rate minus the CPU occupancy rate of the unloaded video; continuously loading 2-4 videos, calculating the average consumption system resource condition of each video, and calculating the system resource required by loading the video pictures configured in the background by multiplying the average consumption system resource condition of each video by the number of the video pictures configured in the background;
step 3: judging the sizes of system idle resources and system resources required by background configuration, if the system idle resources are larger than the system resources required by the background configuration, maintaining the current image quality, and if the system idle resources are smaller than the system resources required by the background configuration, reducing the video image quality;
step 4: judging the system resource occupancy rate after loading all video pictures and the magnitudes of a first threshold value and a second threshold value;
If the video quality is greater than the threshold value I, reducing part of video picture quality until the video quality is lower than the threshold value I, wherein the initial value of the threshold value I is set to be 70%;
If the video picture quality is smaller than the threshold value II, the video picture quality is improved until the video picture quality rises to be higher than the threshold value II and lower than the threshold value I, and the initial value of the threshold value II is set to be 40%;
step 5: monitoring user operation and program response time in real time, judging whether the user operation is abnormal or not, and determining the current page clamping condition;
Under normal conditions, the frame takes about 16ms, and at this time, the user can smoothly interact with the application.
When the frame time is far longer than 16ms, the frame is judged to be stuck, and the following two conditions are simultaneously satisfied when the frame time is far longer than the standard: the current frame time consumption is 2 times the average time consumption of the first three frames,
Current frame time > two-frame movie frame time (1000 ms/24 x 2 = 84 ms).
The user fluency condition judging method comprises the following steps:
From the click, the user, the program responds until the time the UI changes is in line with expectations.
Whether the user sliding operation can normally respond each time, the UI changes as expected.
The user slides and the program responds until the time the UI changes is in line with expectations.
Whether the operations of long press, double click, double finger and the like of the user can be identified normally or not.
Step 6: and modifying the values of the first threshold value and the second threshold value according to whether the page is blocked or not until the most reasonable threshold value and the configuration of all video pictures are calculated, and outputting and displaying.
The modification mode is as follows: when the page is stuck, the threshold I and the threshold II are simultaneously reduced by 5 percent. If the video picture is smooth to play after the video picture is reduced, the user operation is free of blocking, the first threshold value and the second threshold value are the most reasonable threshold values, the system resources are used to the greatest extent, and the user experience is optimal.
When the page is smooth, the threshold I and the threshold II are increased by 5% at the same time, if the video is played and frames are lost after the threshold I and the threshold II are increased, if the user operation has the occurrence of a clamp, the threshold I and the threshold II are restored, and the threshold I and the threshold II are the most reasonable thresholds.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. The visualization method for the intelligent large screen of the video monitoring is characterized by comprising the following steps of:
Step 1: receiving video configuration of a background, monitoring the utilization condition of system resources by loading videos with different resolutions and different code stream types, and recording the utilization condition of the system resources; the system resource use condition is the system CPU occupancy rate;
step 2: after the video is loaded successfully and played normally, calculating system resources consumed by loading the current video configuration according to the current CPU occupancy rate minus the CPU occupancy rate of the unloaded video; continuously loading 2-4 videos, calculating the average consumption system resource condition of each video, and calculating the system resource required by loading the video pictures configured in the background by multiplying the average consumption system resource condition of each video by the number of the video pictures configured in the background;
step 3: judging the sizes of system idle resources and system resources required by background configuration, if the system idle resources are larger than the system resources required by the background configuration, maintaining the current image quality, and if the system idle resources are smaller than the system resources required by the background configuration, reducing the video image quality;
step 4: judging the system resource occupancy rate after loading all video pictures and the magnitudes of a first threshold value and a second threshold value;
If the video quality is greater than the threshold value I, reducing part of video picture quality until the video quality is lower than the threshold value I, wherein the initial value of the threshold value I is set to be 70%;
If the video picture quality is smaller than the threshold value II, the video picture quality is improved until the video picture quality rises to be higher than the threshold value II and lower than the threshold value I, and the initial value of the threshold value II is set to be 40%;
step 5: monitoring user operation and program response time in real time, judging whether the user operation is abnormal or not, and determining the current page clamping condition;
Step 6: modifying the values of the first threshold value and the second threshold value according to whether the page is blocked or not until the most reasonable threshold value and the quality of all video pictures are calculated, and outputting and displaying;
the modification mode is as follows: when the page is blocked, the first threshold value and the second threshold value are reduced by 5% at the same time, if the page is reduced, the video picture is smoothly played, the user operation is free of blocking, at the moment, the first threshold value and the second threshold value are the most reasonable threshold values, at the moment, the system resources are also used to the greatest extent, and the user experience is optimal;
When the page is smooth, the threshold I and the threshold II are increased by 5% at the same time, if the video is played and frames are lost after the threshold I and the threshold II are increased, if the user operation has the occurrence of a clamp, the threshold I and the threshold II are restored, and the threshold I and the threshold II are the most reasonable thresholds.
2. The method for visualizing a video surveillance on a smart large screen according to claim 1, wherein the CPU occupancy rate calculation method is as follows: CPU occupancy= ((appCPUTime 2-appCPUTime 1)/(totalCPUTime 2-totalCPUTime) x 100, appcputime1 indicates the time when the current App process uses the CPU at any moment, appCPUTime2 indicates the time when the App process uses the CPU at any moment, totalCPUTime1 indicates the time when the current system uses the CPU at any moment, and totalCPUTime2 indicates the time when the system uses the CPU at any moment.
3. The method for visualizing a video surveillance on a smart large screen according to claim 1, wherein the specific steps in step 5 are as follows: when a video frame takes much more than 16ms, the following two conditions are satisfied at the same time: and the current frame time consumption is 2 times of the average time consumption of the first three frames, and the current frame time consumption is 2 times of the time consumption of the two frames of video frames, and the current frame time consumption is judged to be the stuck time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310049956.XA CN116156253B (en) | 2023-02-01 | Visualization method for video monitoring on intelligent large screen |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310049956.XA CN116156253B (en) | 2023-02-01 | Visualization method for video monitoring on intelligent large screen |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116156253A CN116156253A (en) | 2023-05-23 |
| CN116156253B true CN116156253B (en) | 2024-06-04 |
Family
ID=
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011150699A1 (en) * | 2010-06-01 | 2011-12-08 | 中兴通讯股份有限公司 | Resource control method for stream media server, and stream media server |
| CN105578073A (en) * | 2015-12-23 | 2016-05-11 | 浙江大华技术股份有限公司 | Video monitoring image display method and device |
| CN106792165A (en) * | 2016-12-02 | 2017-05-31 | 武汉斗鱼网络科技有限公司 | A kind of resource dynamic regulation method and device |
| CN106792169A (en) * | 2016-12-12 | 2017-05-31 | 深圳Tcl数字技术有限公司 | Internet video play handling method and device |
| CN111182352A (en) * | 2018-11-09 | 2020-05-19 | 浙江宇视科技有限公司 | Adaptive code stream control device and method for video playing |
| CN112995654A (en) * | 2021-02-08 | 2021-06-18 | 咪咕音乐有限公司 | Video playing pause detection method and device, server and readable storage medium |
| CN114490215A (en) * | 2022-01-05 | 2022-05-13 | 深圳Tcl新技术有限公司 | Stuck detection method, detection device and computer readable storage medium |
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011150699A1 (en) * | 2010-06-01 | 2011-12-08 | 中兴通讯股份有限公司 | Resource control method for stream media server, and stream media server |
| CN105578073A (en) * | 2015-12-23 | 2016-05-11 | 浙江大华技术股份有限公司 | Video monitoring image display method and device |
| CN106792165A (en) * | 2016-12-02 | 2017-05-31 | 武汉斗鱼网络科技有限公司 | A kind of resource dynamic regulation method and device |
| CN106792169A (en) * | 2016-12-12 | 2017-05-31 | 深圳Tcl数字技术有限公司 | Internet video play handling method and device |
| CN111182352A (en) * | 2018-11-09 | 2020-05-19 | 浙江宇视科技有限公司 | Adaptive code stream control device and method for video playing |
| CN112995654A (en) * | 2021-02-08 | 2021-06-18 | 咪咕音乐有限公司 | Video playing pause detection method and device, server and readable storage medium |
| CN114490215A (en) * | 2022-01-05 | 2022-05-13 | 深圳Tcl新技术有限公司 | Stuck detection method, detection device and computer readable storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 基于iOS平台的移动视频监控软件设计;肖远东;蔡声镇;;计算机工程;20150215(第02期);全文 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8699818B2 (en) | Method, system, and program for determining image quality based on pixel changes between image frames | |
| US10362264B2 (en) | Profile for frame rate conversion | |
| CN110830787B (en) | Method and device for detecting screen-patterned image | |
| CN111182352B (en) | Adaptive code stream control device and method for video playing | |
| CN111327908A (en) | Video processing method and related device | |
| CN105898348A (en) | Method and device for reducing CPU temperature of video play terminal | |
| US6697431B1 (en) | Image signal decoder and image signal display system | |
| CN107613302B (en) | Decoding method and device, storage medium and processor | |
| CN114827662A (en) | Video resolution self-adaptive adjusting method, device, equipment and storage medium | |
| CN112788329A (en) | Video static frame detection method and device, television and storage medium | |
| CN109587561B (en) | Video processing method and device, electronic equipment and storage medium | |
| CN111405347B (en) | Picture display method and device, electronic equipment and readable storage medium | |
| CN116156253B (en) | Visualization method for video monitoring on intelligent large screen | |
| CN110012315A (en) | A kind of video broadcasting method, device and electronic equipment | |
| CN112203097A (en) | Adaptive video decoding method and device, terminal equipment and storage medium | |
| CN116156253A (en) | Visualization method for video monitoring on intelligent large screen | |
| CN108074248B (en) | OSD automatic detection method and device based on image content | |
| CN110300326B (en) | Video jamming detection method and device, electronic equipment and storage medium | |
| WO2020038071A1 (en) | Video enhancement control method, device, electronic apparatus, and storage medium | |
| JP4182747B2 (en) | Image processing apparatus, image processing method, image processing program, and recording medium | |
| CN113709447B (en) | Method and device for detecting playing performance of terminal equipment | |
| Grbić et al. | Real-time video freezing detection for 4K UHD videos | |
| JP5179433B2 (en) | Noise reduction device, noise reduction method, and moving image playback device | |
| CN115002520B (en) | Video stream data processing method, device, equipment and storage medium | |
| JP2006060335A (en) | Image processing apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |