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Proceedings Paper

Detection function and its application in visual tracking
Author(s): Yiming Ye; John K. Tsotsos; Karen Bennet; Eric Harley
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Paper Abstract

This paper introduces the concept of detection function for assessing recognition algorithms. A detection function specifies the probability that a particular recognition algorithm will detect the target, given the camera viewing direction and angle size and the target position. The detection function thus determines the region of space in which the target can be detected with high probability using certain specified camera parameters. For this reason, it provides a natural language for discussion of the task of tracking an object moving in 3D using a camera with adjustable pan, tilt, and zoom. Most previous studies on visual tracking involve the use of a camera with fixed viewing direction and viewing angle size. We advocate, however, an algorithm wherein these camera parameters are actively controlled to keep the target in the field of view and to maintain its image quality. In this paper we study geometrical issues related to the detection function and describe a novel tracking algorithm.

Paper Details

Date Published: 20 October 1997
PDF: 10 pages
Proc. SPIE 3168, Vision Geometry VI, (20 October 1997); doi: 10.1117/12.279662
Show Author Affiliations
Yiming Ye, IBM Thomas J. Watson Research Ctr. (Canada)
John K. Tsotsos, Univ. of Toronto (Canada)
Karen Bennet, IBM Ctr. for Advanced Studies (Canada)
Eric Harley, Univ. of Toronto (Canada)


Published in SPIE Proceedings Vol. 3168:
Vision Geometry VI
Robert A. Melter; Angela Y. Wu; Longin Jan Latecki, Editor(s)

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