Video behavior timeline detection method
A detection method and time axis technology, applied in the field of video analysis, can solve problems such as insufficient use of candidate frames and efficiency to be improved
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2018-11-16
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Abstract
Description
technical field
[0001] The present invention relates to the technical field of video analysis, in particular to a video behavior timeline detection method, which is based on deep learning and combined with video context information to detect the timeline of human behavior in a video. Background technique
[0002] Videos containing human behavior can be divided into two categories: one is artificially cropped video containing only human behavior without any extraneous background video; the other is uncropped video after shooting, in which not only Includes human behavior and contains extraneous background segments such as credits, audience, etc. Video behavior timeline detection refers to locating the start time and end time of human behavior in a video that has not been manually cropped, and identifying the category of human behavior. The existing video behavior timeline detection methods mainly follow a two-step strategy: first, extract a large number of video behavior tim...
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Embodiment Construction
[0029] Below in conjunction with accompanying drawing, further describe the present invention through embodiment, but do not limit the scope of the present invention in any way.
[0030] Video behavior timeline detection is a subproblem of video behavior detection, which mainly focuses on locating the beginning and end of time when behaviors occur within a video. It plays a key technical support role in the fields of intelligent monitoring system, human-computer interaction and video search. Since the video contains a lot of information, most of which are useless noise, it is very important to automatically locate the video segments of human interest on the time axis for subsequent processing before processing. In practical applications, quite high requirements are placed on the accuracy of video behavior positioning. In order to accurately locate the start time and end time of a video action, it is very important to extract the time boundary information of the action. This ...