Method for extracting video interested region based on visual attention

Abstract

The invention discloses a method for extracting a video interested region based on a visual attention. The interested region extracted by the method combines a static image domain visual attention, amotion visual attention and a depth perception attention, and the method efficiently restrains the internal unicity and inaccuracy of each visual attention extraction and solves the problem of noisescaused by a complex background in the static image domain visual attention and the problem that the motion visual attention can not extract an interested region with small local motion and motion amplitude, thus the method improves the calculation accuracy, enhances the algorithm stability and extracts an interested region from a background with complex veins and the motion environment; furthermore, the interested region obtained by the method accords with the depth perception feature interesting on an object having a strong depth perception or a short distance in the stereovision and the semantic characteristic of human eye stereovision besides according with the vision feature of human eye interesting a static grain video frame and interesting a motion object.

Description

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AI Technical Summary

Problems solved by technology

[0004] However, the current automatic region of interest extraction is mainly divided into three categories, 1) using the internal information of a single viewpoint image, including stimulus information such as brightness, color, texture or direction, to extract the region of interest of the human eye on the current video frame, This method mainly extracts regions with large differences in brightness, color and texture contrast as regions of interest, which makes this method difficult to apply to the region of interest extraction in complex background environments; The principle is to use the motion information between video frames as the main clue to extract the region of interest. However, this method is difficult to accurately extract slow or local moving objects, and it is also difficult to apply to the region of interest extraction in the case of global motion; 3 ), using the extracti

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