Segmentation Tracking and Recognition Based on Foreground-Background Absolute Features, Simplified SIFT, and Particle Filters

We propose an approach to tracking and recognition based on segmentation by scanning foreground-background absolute difference (FBAD) features, simplified scale-invariant feature transform (s-SIFT), and evolutionary particle filter. Particle filter is shown to be efficient in visual tracking due to...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Yong-Gun Jo, Ja-Yong Lee, Hoon Kang
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Active contours Bayesian methods Intelligent robots Level measurement Machine intelligence Particle filters Particle tracking Robot vision systems Shape Target tracking
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