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Stochastic Pedestrian Tracking Based on 6-Stick Skeleton Model
Ryusuke MIYAMOTO Jumpei ASHIDA Hiroshi TSUTSUI Yukihiro NAKAMURA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2007/03/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Multimedia and Mobile Signal Processing)
pedestrian tracking, particle filter, skeleton, distance transformation,
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A novel pedestrian tracking scheme based on a particle filter is proposed, which adopts a skeleton model of a pedestrian for a state space model and distance transformed images for likelihood computation. The 6-stick skeleton model used in the proposed approach is very distinctive in representing a pedestrian simply but effectively. By the experiment using the real sequences provided by PETS, it is shown that the target pedestrian is tracked adequately by the proposed approach with a simple silhouette extraction method which consists of only background subtraction, even if the tracking target moves so complicatedly and is often so cluttered by other obstacles that the pedestrian can not be tracked by the conventional methods. Moreover, it is demonstrated that the proposed scheme can track the multiple targets in the complex case that their trajectories intersect.