Motion segmentation and pose recognition with motion history gradients

  • Authors:
  • Gary R. Bradski;James W. Davis

  • Affiliations:
  • Microcomputer Research Labs, Intel Corporation, Ohio State University, SC12-303, 2200 Mission College Blvd., Santa Clara, CA;Department of Computer and Information Science, 583 Dreese Lab, 2015 Neil Ave, Columbus, OH

  • Venue:
  • Machine Vision and Applications - Special issue: IEEE WACV
  • Year:
  • 2002

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Abstract

This paper presents a fast and simple method using a timed motion history image (tMHI) for representing motion from the gradients in successively layered silhouettes. This representation can be used to (a) determine the current pose of the object and (b) segment and measure the motions induced by the object in a video scene. These segmented regions are not "motion blobs", but instead are motion regions that are naturally connected to parts of the moving object. This method may be used as a very general gesture recognition "toolbox". We demonstrate the approach with recognition of waving and overhead clapping motions to control a music synthesis program.