2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:WA-L2.8
Session:Video Object Segmentation and Tracking II
Time:Wednesday, September 19, 12:30 - 12:50
Presentation: Lecture
Title: ON UNCERTAINTIES, RANDOM FEATURES AND OBJECT TRACKING
Authors: Vijay Badrinarayanan; Thomson Corporate Research 
 Patrick Perez; IRISA-INRIA Rennes 
 François Le Clerc; Thomson Corporate Research 
 Lionel Oisel; Thomson Corporate Research 
Abstract: Algorithms for probabilistic visual tracking hypothesize a distribution of the target state (location, scale, etc.)at every tracking step with an associated information content or equivalently, an uncertainty. One measure of this uncertainty is the differential entropy. In this paper, we present a unified way to approximate the differential entropy of tracking distributions, which then makes it suitable, among other factors, for a qualitative assessment of both deterministic and sequential Monte Carlo simulation based tracking algorithms. We then illustrate the usefulness of this assessment measure via tracking an object by choosing a set of randomly picked features on it, each individually tracked, removed according to an uncertainty analysis and replaced randomly, without any aid of a feature selection algorithm as in current use.



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