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2009
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Rapid And Robust Human Detection And Tracking Based On Omega-shape Features

12 years 2 months ago
Rapid And Robust Human Detection And Tracking Based On Omega-shape Features
This paper proposes a novel method for rapid and robust human detection and tracking based on the omega-shape features of people's head-shoulder parts. There are two modules in this method. In the first module, a Viola-Jones type classifier and a local HOG (Histograms of Oriented Gradients) feature based AdaBoost classifier are combined to detect headshoulders rapidly and effectively. Then, in the second module, each detected head-shoulder is tracked by a particle filter tracker using local HOG features to model target's appearance, which shows great robustness in scenarios of crowding, background distractors and partial occlusions. Experimental results demonstrate the effectiveness and efficiency of the proposed approach.
Added 10 Nov 2009
Updated 26 Dec 2009
Type Conference
Year 2009
Where ICIP
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