Noise estimation and adaptive filtering during visual tracking

Authors:
Ibrahima J. Ndiour;Patricio A. Vela
Affiliations:
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA;School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

This paper proposes a procedure to characterize segmentation-based visual tracking performance with respect to imaging noise. It identifies how imaging noise affects the target segmentation as measured through local shape metrics (Sobolev and Laplace metrics). Such a procedure would be an important calibration step prior to implementing a visual tracking filter for a given need. We utilize the Bhattacharyya coefficient between the target and background intensity distributions to estimate the segmentation error. An empirical study is conducted to establish a correspondence between the Bhattacharyya coefficient and the segmentation error. The correspondence is used to adaptively filter temporally correlated segmentations. Preliminary results show improved performance when compared to fixed gains.