Optical flow-based gesture motion direction recognition method

Abstract

The invention discloses an optical flow-based gesture motion direction recognition method. The method comprises the following steps of acquiring an image sequence on the front of a computer by using a common camera with video graphics array resolution, and preprocessing the image sequence; distributing skin samples in an approximately elliptical area in a CbCr plane in a concentrated way, and determining whether to accord with skin colors according to a fact whether a pixel point falls in the elliptical area in the CbCr plane; performing morphological reconstruction on binary images subjected to skin color detection, and adopting closed operation in morphology; marking each white connected region, calculating an area of each white connected region, arraying white connected regions from large to small, and reserving three largest connected regions; reducing the resolution of the images, and acquiring an optical flow motion vector in a skin color area by using a pyramid LK optical flow method; judging the direction of the optical flow motion vector; judging the direction once every other two frames, and giving a result if directions are consistent twice; after a user is familiar with and masters the gesture motion operation rule, moving the gesture in the upper, lower, left and right directions before the camera. According to the method, real-time interaction can be completed, and the gesture motion direction recognition accuracy can be higher than 95 percent.

Description

technical field [0001] The invention relates to a gesture movement direction recognition method based on an optical flow method, which belongs to the field of computer vision. Background technique [0002] Simple mechanical devices such as mice, keyboards, and handwriting tablets are the most commonly used human-computer interaction methods, but these human-computer interaction methods are computer-centric, not humanized enough and have great limitations, and are not enough to satisfy people. needs. The hand is one of the most flexible parts of the human body. Gestures are widely used in daily communication and operation, which is convenient and quick. Gestures are human-centered and conform to people's living habits, so gestures are of great research value as a new type of human-computer interaction. [0003] Existing research on gesture recognition based on computer vision generally recognizes different gestures of gestures to give different meanings, such as using hidde...

AI Technical Summary

Problems solved by technology

Studying the motion direction recognition of gestures can reduce the data that the computer needs to process. It is not as complicated as the gesture posture research, but there are few researches on the recognition of gesture motion direction.

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