Support vector tracking

Support vector tracking

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,...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 2004-08, Vol.26 (8), p.1064-1072
1. Verfasser: Avidan, S.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Artificial Intelligence
Brightness
Cameras
Computer Graphics
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image sequences
Imaging, Three-Dimensional - methods
Information Storage and Retrieval - methods
Integrated optics
Movement
Numerical Analysis, Computer-Assisted
optic-flow
Optical filters
Optical sensors
Pattern Recognition, Automated - methods
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Subtraction Technique
Support vector machine classification
Support vector machines
Vehicle detection
Video Recording - methods
Video sequences
visual tracking
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Beschreibung
Zusammenfassung: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.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2004.53