Using Gaussian Process Annealing Particle Filter for 3D Human Tracking. (20th January 2008)

• Record Type: Journal Article
• Authors: Raskin Raskin, Leonid Leonid; Rivlin Rivlin, Ehud Ehud; Rudzsky Rudzsky, Michael Michael
• Other Names: Çetin Çetin Enis Ahmet Enis Ahmet Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-01-20
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/592081
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian process annealing particle filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker's stability and robustness. Comparing with a regular annealed particle filter-based tracker, we show that our algorithm can track better for low frame rate videos. We also show that our algorithm is capable of recovering after a temporal target loss.