Gesture recognition method and device

Abstract

The invention discloses a gesture recognition method. The method comprises the steps that common human body basic actions are captured and are stored as sample actions; according to the sample actions, final training actions are obtained; graphics rendering is conducted on the training actions and a preliminary depth map and a corresponding position identification graph are generated; according to the generated depth map, samples similar to the depth map collected in real time are synthesized; the synthesized samples are used for calculating corresponding depth characteristic vectors, and a random forest model is obtained through training; accurate depth figure outline is extracted through area growth based on smoothness constraining; depth characteristic vectors of each pixel of the depth figure outline are calculated based on the random forest model, and position identification probability of each pixel is determined through the random forest model; noisy points are filtered and identified based on the human body part corresponding to each pixel and the probability of each pixel, and skeleton nodes are generated in a polymerized mode; a time-sequential sequence of the skeleton nodes is recorded and a skeleton motion track is generated; the motion tracks of the nodes of the hands are extracted and are matched with a predefined template, and the gesture action type is recognized. The invention further discloses a gesture recognition device.

Description

technical field [0001] The present invention relates to gesture recognition technology, in particular to a gesture recognition method and device. Background technique [0002] Vision-based somatosensory interaction technology has attracted more and more attention from researchers in recent years, especially since Microsoft released Kinect, a somatosensory interaction device solution that can support whole-body gesture recognition, and researchers have seen the future of somatosensory interaction technology. Application prospects. In recent years, a large number of scholars, research institutions and related companies have been engaged in the exploration and research of somatosensory interaction, which can be roughly divided into two aspects: one is close-range action interaction, which captures smaller areas and objects, and focuses on hand gestures, such as SixthSense etc.; one is whole-body motion interaction, and the range of motion is larger, which requires a larger cap...

AI Technical Summary

Problems solved by technology

[0005] Microsoft's somatosensory interaction device Kinect uses the direction judgment and prediction of the motion trajectory to recognize gestures. Although this method can accurately recognize gestures, it has a large amount of calculation and takes a long time. It cannot be used on JAVA-based Android platform tablet computers. , and IPTV TV set-top boxes

At the same time, Microsoft's skeleton aggregation recognition tool NITE middleware is not open source, and there are difficulties in the development of action recognition

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