Method and system for automatically extracting gesture candidate region in video sequence

Abstract

The invention discloses a method for automatically extracting a gesture candidate region in a video sequence. The method comprises the following steps of: enabling a gesture video image acquisition system to acquire video images; constructing reference background images; computing to generate motion description images; computing to obtain motion segmentation threshold values and converting the motion description images into binary motion images; conducting skin color segmentation to obtain binary skin color images; conducting logic and operation to the binary motion images and the binary skin color images point by point to obtain binary fused images; and conducting connected region analysis to the binary fused images and selecting the gesture candidate region. The method combines motion information with skin color information to find the gesture candidate region, the two kinds of information complement each other, the detection accuracy is improved, the method is practical and effective and a very good foundation is provided for the segmentation, the positioning and the recognition of gestures.

Description

technical field [0001] The invention belongs to the technical field of intelligent information processing, and relates to a method for automatically extracting gesture candidate regions in a video sequence, which is applied to digital video image analysis and understanding. Background technique [0002] Traditional human-computer interaction methods, such as mouse, keyboard, remote control, etc., are human beings adapting to computers and completing interactive tasks according to preset specifications. In recent years, with the continuous development of technology, the processing power of computers has become stronger and stronger, and people have begun to study natural human-computer interaction technology that conforms to human communication habits, gradually shifting from computer-centered to human-centered. These studies include speech recognition, face and expression recognition, head movement tracking, gaze tracking, gesture recognition, body gesture recognition, and m...

AI Technical Summary

Problems solved by technology

Most of the other gesture recognition technologies only rely on skin color information for gesture detection and segmentation. In these technologies, it is often assumed that the hand is the only or the largest skin color area in the entire image; in addition, some researchers use motion information to perform gesture detection. The detection localization of , which also assumes that the hand is the only or the largest motion area in the entire image

However, the above two methods are only effective in simple application scenarios, and the actual application scenarios are generally more complex and cannot meet the assumptions, so it is difficult to achieve the effect

In some gesture recognition systems using template matching technology, there is no separate detection and positioning stage, and the preset gesture templates are used to traverse the entire image to find the best matching position and complete detection, positioning and recognition at the same time. However, this traversal method heavy calculation

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