Video quality diagnosis processing method and apparatus

Abstract

The embodiment of the invention provides a video quality diagnosis processing method and apparatus. The method comprises the following steps: S101: collecting a video quality parameter of a video image output by an image device every preset time period; S102: obtaining a video quality parameter regression function according to the video quality parameters collected from the ith moment to the (i+n)th moment; wherein i is greater than or equal to 1, and n is a preset constant; S103: calculating a video quality parameter prediction value corresponding to the video quality parameter collected at the (i+n+1)th moment according to the video quality parameter regression function; S104: calculating a video quality deviation value according to the video quality parameter collected at the (i+n+1)thmoment and the video quality parameter prediction value corresponding to the video quality parameter collected at the (i+n+1)th moment; and S105: performing video quality diagnosis according to the video quality deviation value. The apparatus is used for executing the method. By adoption of the method and the apparatus provided by the embodiment of the invention, the video quality diagnosis efficiency is improved.

Description

technical field [0001] Embodiments of the present invention relate to the field of computer technology, and in particular, to a method and device for video quality diagnosis and processing. Background technique [0002] Using video quality diagnosis technology to intelligently analyze the video data of surveillance cameras, replacing manual inspections for troubleshooting, has gradually become one of the important methods for the operation and maintenance of video surveillance systems. Therefore, research on the efficiency of video quality diagnosis is also increasing. received people's attention. [0003] In the face of complex and changeable video surveillance scenarios (for example, an effective video quality diagnosis system that works on sunny days may not be able to accurately report the status of the camera in rainy days, and the video quality status of the same camera at night is quite different from that during the day. ), the time span of the video image output by...

AI Technical Summary

Problems solved by technology

[0003] In the face of complex and changeable video surveillance scenarios (for example, an effective video quality diagnosis system that works on sunny days may not be able to accurately report the status of the camera in rainy days, and the video quality status of the same camera at night is quite different from that during the day. ), the time span of the video image output by the camera is large, in order to reduce the error of the video quality diagnosis result as much as possible, the existing video diagnosis technology often forms a lens group with cameras of the same model and similar installation environment, and uses For the same set of video diagnosis algorithms, different video diagnosis algorithms are used for scenes with different time spans. For example, indoor cameras are placed in a group, and a set of algorithms is used separately during the day and at night, which greatly affects the quality of video diagnosis. efficiency

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