Paper
14 March 2005 A complete system for head tracking using motion-based particle filter and randomly perturbed active contour
N. Bouaynaya, Dan Schonfeld
Author Affiliations +
Proceedings Volume 5685, Image and Video Communications and Processing 2005; (2005) https://doi.org/10.1117/12.587244
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
Recent advances in multimedia and communication require techniques for accurately tracking objects in video sequences. We propose a complete system for head tracking and contour refinement. Our tracking approach is based on particle filtering framework. However, unlike existing methods that use prior knowledge or likelihood functions as proposal densities, we use a motion-based proposal. Adaptive Block Matching (ABM) algorithm is the motion estimation technique used. Several advantages arise from this choice of proposal. (i) Only few samples are propagated. (ii) The tracking is adaptive to different categories of motion (iii) Off-line motion learning is not needed. Following the tracking is the contour refinement step. We want to transform the parametric estimate representing the tracked head at a given time instant into an elastic contour delineating the head’s boundaries. We use an active contour framework based on a dynamic programming scheme. However active contours are very sensitive to parameter assignment and initial condition. Using the tracked parametric estimate, we create a set of randomly perturbed initial conditions. The optimal contour is then the one corresponding to the lowest energy. Our system demonstrates tracking a person’s head in complex environments and delineates its boundaries for future use.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
N. Bouaynaya and Dan Schonfeld "A complete system for head tracking using motion-based particle filter and randomly perturbed active contour", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); https://doi.org/10.1117/12.587244
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CITATIONS
Cited by 18 scholarly publications and 4 patents.
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KEYWORDS
Head

Particle filters

Particles

Detection and tracking algorithms

Motion models

Video

Motion estimation

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