Support Vector Tracking

By Shai Avidan. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001

329 citations recorded by the source corpus.

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Object tracking: A survey (2006, methodology): “In a similar vein, Avidan [2001] used a Support Vector Machine (SVM) classifier for tracking.”
Detecting Pedestrians Using Patterns of Motion and Appearance (2003, neutral): “Examples include face, automobile, and pedestrian detection (Viola and Jones, 2001; Rowley et al., 1998; Schneiderman and Kanade, 2000; Avidan, 2001; Papageorqiou et al., 1998).”
Visual Object Tracking for Unmanned Aerial Vehicles: A Benchmark and New Motion Models (2017, methodology): “Deterministic methods such as tracking-by-detection (Avidan 2004; Danelljan et al. 2014; Ma et al. 2015) usually adopt the sliding window approach to exhaustively search for the best candidate within a region.”
Real-time visual tracking using compressive sensing (2011, background): “A few attempts have been made along this line in the literature [1, 2, 3, 4].”