A motion observable representation using color correlogram and its applications to tracking

Qi Zhao, Hai Tao

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

This paper presents a special form of color correlogram as representation for object tracking and carries out a motion observability analysis to obtain the optimal correlogram in a kernel based tracking framework. Compared with the color histogram, where the position information of each pixel is ignored, a simplified color correlogram (SCC) representation encodes the spatial information explicitly and enables an estimation algorithm to recover the object orientation. In this paper, based on the SCC representation, the mean shift algorithm is developed in a translation-rotation joint domain to track the positions and orientations of objects. The ability of the SCC in detecting and estimating object motion is analyzed and a principled way to obtain the optimal SCC as object representation is proposed to ensure reliable tracking. Extensive experimental results demonstrate SCC as a viable object representation for tracking.

Original languageEnglish (US)
Pages (from-to)273-290
Number of pages18
JournalComputer Vision and Image Understanding
Volume113
Issue number2
DOIs
StatePublished - Feb 2009

Keywords

  • Kernel based tracking
  • Optimal feature selection
  • Simplified color correlogram (SCC)

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