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2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance
Dynamic Models for People Detection and Tracking
September 01-September 03
ISBN: 978-0-7695-3341-4
In this paper we propose a real-time algorithm for detecting and tracking moving objects in a video sequence. Based on the on-line boosting framework, our algorithm is able to detect an object as a member of a class, e.g. pedestrian, then a specific model for each instance of the class can be built on-line allowing at the same time robust tracking and recognition of the particular instance as it leaves and re-enters the scene. Promising experimental results have been performed on standard video sequences.
Index Terms:
Online boosting, detection, tracking, recognition, video surveillance
Citation:
Lauro Snidaro, Ingrid Visentini, Gian Luca Foresti, "Dynamic Models for People Detection and Tracking," avss, pp.29-35, 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, 2008
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