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Type: Journal article
Title: Adaptive object tracking based on an effective appearance filter
Author: Wang, H.
Suter, D.
Schindler, K.
Shen, C.
Citation: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007; 29(9):1661-1667
Publisher: IEEE Computer Soc
Issue Date: 2007
ISSN: 0162-8828
Statement of
Hanzi Wang, David Suter, Konrad Schindler and Chunhua Shen
Abstract: We propose a similarity measure based on a Spatial-color Mixture of Gaussians (SMOG) appearance model for particle filters. This improves on the popular similarity measure based on color histograms because it considers not only the colors in a region but also the spatial layout of the colors. Hence, the SMOG-based similarity measure is more discriminative. To efficiently compute the parameters for SMOG, we propose a new technique with which the computational time is greatly reduced. We also extend our method by integrating multiple cues to increase the reliability and robustness. Experiments show that our method can successfully track objects in many difficult situations.
Keywords: Image Interpretation, Computer-Assisted
Image Enhancement
Models, Statistical
Sensitivity and Specificity
Normal Distribution
Reproducibility of Results
Artificial Intelligence
Computer Simulation
Pattern Recognition, Automated
DOI: 10.1109/TPAMI.2007.1112
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Appears in Collections:Aurora harvest 5
Computer Science publications

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