Severe motion detection method based on multi-eye stereo vision scene flow

Abstract

The invention provides a multi-view stereo vision scene stream-based strenuous exercise detection method which comprises the following steps: I: acquiring multiple groups of image sequences by using a calibrated multi-view camera; II: preprocessing the image sequences; III: designing a scene stream energy function data item; IV: designing a scene stream energy function smoothing item; V: optimally solving an energy function, and performing calculation with a calculation model from an image with the lowest resolution in an image pyramid obtained in the step II; VI: clustering a scene stream exercise region; VII: constructing an exercise direction discrete degree estimation model to judge whether an exercise is a strenuous exercise; VIII: constructing an exercise region kinetic energy size estimation model; and XI: setting a threshold value, and triggering an alarm when continuous n frames meet an estimation condition. By adoption of multi-view stereo vision scene stream-based estimation, the multiple groups of image sequences of the same scene are acquired by using the calibrated multi-view camera, and the strenuous exercise can be effectively detected by using a three-dimensional scene stream.

Description

technical field [0001] The present invention relates to a method for detecting violent motion, in particular to a method for detecting violent motion based on multi-eye stereoscopic scene flow. Background technique [0002] With the high development of today's science and technology information technology, especially the breakthroughs made by humans in computer vision and artificial intelligence, many tasks that should be done by humans can be done by computers. For example, in video surveillance, the most common method of operation is for people to observe the monitor display, and then respond accordingly to abnormal events that occur. Since people cannot concentrate on monitoring all the events in the video for a long time, the phenomenon of missed alarms will inevitably occur. Therefore, it is particularly important to use a computer to process video frames and judge whether abnormal events occur. [0003] In general, the position of the video surveillance camera is fix...

AI Technical Summary

Problems solved by technology

In the absence of depth information, it is difficult to evaluate and judge the detection of violent motion, which is likely to cause false alarms and missed alarms

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