Probabilistic center voting method for subsequent object tracking and segmentation

Suryanto, Hyo Kak Kim, Sang Hee Park, Dae Hwan Kim, Sung Jea Ko

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new frame to cast a vote on whereabouts the object center is. The back projection method segments the object from the background. The segmented foreground provides information on object size and orientation, omitting the need to estimate them separately. We do not put any assumption on camera motion; the proposed algorithm works equally well for object tracking in both static and moving camera videos.

Original languageEnglish
Pages (from-to)450-454
Number of pages5
JournalWorld Academy of Science, Engineering and Technology
Volume59
Publication statusPublished - 2009 Nov

Keywords

  • Back projection
  • Center voting
  • Non-stationary camera tracking
  • Object tracking
  • Size adaptation

ASJC Scopus subject areas

  • Engineering(all)

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