Support Vector Tracking

Shai Avidan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Support Vector Tracking (SVT) integrates the Support Vector Machine (SVM) classifier into an optic-flow-based tracker. Instead of minimizing an intensity difference function between successive frames, SVT maximizes the SVM 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 SVT for vehicle tracking in image sequences.

Original languageEnglish
Pages (from-to)1064-1072
Number of pages9
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number8
StatePublished - Aug 2004
Externally publishedYes


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