Efficient region tracking with parametric models of geometry and illumination

Gregory D. Hager, Peter N. Belhumeur

Research output: Contribution to journalArticlepeer-review

Abstract

As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the image plane. Rather, complications arise due to the fact that the object undergoes changes in pose relative to the viewing camera, changes in illumination relative to light sources, and may even become partially or fully occluded. In this paper, we develop an efficient, general framework for object tracking-one which addresses each of these complications. We first develop a computationally efficient method for handling the geometric distortions produced by changes in pose. We then combine geometry and illumination into an algorithm that tracks large image regions using no more computation than would be required to track with no accommodation for illumination changes. Finally, we augment these methods with techniques from robust statistics and treat occluded regions on the object as statistical outliers. Throughout, we present experimental results performed on live video sequences demonstrating the effectiveness and efficiency of our methods.

Original languageEnglish (US)
Pages (from-to)1025-1039
Number of pages15
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume20
Issue number10
DOIs
StatePublished - 1998
Externally publishedYes

Keywords

  • Illumination
  • Motion estimation
  • Real-time vision
  • Robust statistics. © 1998 ieee
  • Visual tracking

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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