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Issue No.08 - August (2004 vol.26)
pp: 1064-1072
<p><b>Abstract</b>—Support Vector Tracking (<b>SVT</b>) integrates the Support Vector Machine (<b>SVM</b>) classifier into an optic-flow-based tracker. Instead of minimizing an intensity difference function between successive frames, <b>SVT</b> maximizes the <b>SVM</b> classification score. To account for large motions between successive frames, we build pyramids from the support vectors and use a coarse-to-fine approach in the classification stage. We show results of using <b>SVT</b> for vehicle tracking in image sequences.</p>
Support vector machines, optic-flow, visual tracking.
Shai Avidan, "Support Vector Tracking", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.26, no. 8, pp. 1064-1072, August 2004, doi:10.1109/TPAMI.2004.53
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