Robust motion estimation under varying illumination

  • Authors:

  • Yeon-Ho Kim;Aleix M. Martínez;Avi C. Kak

  • Affiliations:

  • School of Electrical and Computer Engineering, Purdue University, 2015 Neil Avenue, Columbus, OH 43210, USA;Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA;School of Electrical and Computer Engineering, Purdue University, 2015 Neil Avenue, Columbus, OH 43210, USA

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2005

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Abstract

The optical-flow approach has emerged as a major technique for estimating scene and object motion in image sequences. However, the results obtained by most optical flow techniques are strongly affected by motion discontinuities and by large illumination changes. While there do exist many separate techniques for robust estimation of optical flow in the presence of motion discontinuities and for dealing with the problems caused by illumination variations, only a few integrated approaches have been proposed. However, most of these previously proposed integrated approaches use simple models of illumination variation; a common assumption being that illumination changes by either just a multiplicative factor or just an additive factor from frame to frame, but not both. Some other previously proposed integrated approaches are limited to specialized tasks such as image registration or change recovery. To remedy this shortcoming, this paper presents a new robust approach to general motion estimation in an integrated framework. Our approach deals simultaneously with motion discontinuities and large illumination variations. Our model of illumination variation is general, in the sense that it admits both multiplicative and additive effects.