conference paper

Conference/Proceedings9th IEEE International Conference on Advanced Video and Signal-Based Surveillance
Start date18.09.2012
End date21.09.2012
AddressBeijing, China
Author(s)Michael Pätzold, Rubén Heras Evangelio, Thomas Sikora
TitleBoosting Multi-Hypothesis Tracking by means of Instance-specific Models
AbstractIn 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.
Key wordsMulti Object Tracking MHT Adaboost
NoteISBN: 978-1-4673-2499-1