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Boosting Multi-Hypothesis Tracking by means of Instance-specific Models
Citation key 1368Pätzold2012
Author Michael Pätzold and Rubén Heras Evangelio and Thomas Sikora
Title of Book 9th IEEE International Conference on Advanced Video and Signal-Based Surveillance
Year 2012
DOI 10.1109/AVSS.2012.18
Address Beijing, China
Month sep
Note ISBN: 978-1-4673-2499-1
Abstract In this paper we present a visual person tracking-by-detection system based on on-line-learned instance-specific information along with the kinematic relation of measurements provided by a generic person-category detector. The proposed system is able to initialize tracks on individual persons and start learning their appearance even in crowded situations and does not require that a person enters the scene separately. For that purpose we integrate the process of learning instance-specific models into a standard MHT-framework. The capability of the system to eliminate detections-to-object association ambiguities occurring from missed detections or false ones is demonstrated by experiments for counting and tracking applications using very long video sequences on challenging outdoor scenarios.
Link to publication [1] Download Bibtex entry [2]
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