Human tracking and silhouette extraction for human-robot interaction systems

Jung Ho Ahn, Cheolmin Choi, Sooyeong Kwak, Kilcheon Kim, Hyeran Byun

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

In this study, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with a pan-tilt stereo camera, so that it can assist in gesture and gait recognition in the field of Human-Robot Interaction (HRI). The proposed system consists of three modules: detection, tracking and silhouette extraction. These modules are robust to camera movements, and they work interactively in near real-time. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift-based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap was estimated in advance and then effectively incorporated into the graph-cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data, and it was shown to detect and track multiple people very well and also produce high-quality silhouettes.

Original languageEnglish
Pages (from-to)167-177
Number of pages11
JournalPattern Analysis and Applications
Volume12
Issue number2
DOIs
Publication statusPublished - 2009 Jun 1

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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