Object locomotion mode identification method and device based on depth image sequence

Abstract

Provided is an object locomotion mode identification method based on a depth image sequence. The method comprises a foreground determining step of determining a foreground object area in every depth image frame; a difference step of calculating difference between depth values of every pixel in every depth image frame and depth values of neighborhood pixels of the pixel so as to obtain difference vectors of the neighborhood depth values; a quantization coding step of determining an area of interest according to the foreground object area and enabling the difference vectors of the neighborhood depth values of every pixel in the area of interest to undergo quantization coding to become neighborhood depth value differential codes; an area division step of dividing the area of interest into a plurality of subareas; a distribution description step of obtaining neighborhood depth value differential code distribution characteristic vectors of the subareas; and an identification step of identifying a locomotion mode of an object corresponding to the area of interest according to combination of the neighborhood depth value differential code distribution characteristic vectors. An object locomotion mode identification device based on the depth image sequence is further provided correspondingly.

Description

technical field [0001] The invention relates to an object motion pattern recognition method based on a depth image sequence and an object motion pattern recognition device based on a depth image sequence. Background technique [0002] With the development of computer vision, image processing, and human-computer interaction technology, there are more and more technical requirements for vision-based human-computer interaction systems, such as interactive projectors, interactive displays, interactive electronic whiteboards, and somatosensory game consoles. More urgently, in these application areas, not only the recognition of objects in images is often required, but also the recognition of object motion patterns. In this regard, certain progress has been made in related technical fields. [0003] Patent Document 1 (US 7,274,800 B2) proposes a technique of using a depth disparity map generated by a stereo camera and performing gesture recognition based on the depth disparity ma...

AI Technical Summary

Problems solved by technology

Because motion can cause blurring of the depth map, thereby affecting the accuracy of the shape, the method is limited to shape description, making it unsuitable for motion gesture recognition

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