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 a homogeneous quadratic polynomial kernel-SVT for vehicle tracking in image sequences.
Support Vector Tracking
2001-01-01
1216803 byte
Conference paper
Electronic Resource
English
British Library Conference Proceedings | 2001
|One-class support vector machine-assisted robust tracking
British Library Online Contents | 2013
|Improving Particle Filter with Support Vector Regression for Efficient Visual Tracking
British Library Conference Proceedings | 2005
|Tracking support apparatus, tracking support system, and tracking support method
European Patent Office | 2017