title   
  

Tracklet clustering for robust multiple object tracking using distance dependent Chinese restaurant processes

Topkaya, İbrahim Saygın and Erdoğan, Hakan and Porikli, Fatih (2015) Tracklet clustering for robust multiple object tracking using distance dependent Chinese restaurant processes. Signal, Image and Video Processing . pp. 1-8. ISSN 1863-1703 (Print) 1863-1711 (Online)

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Official URL: http://dx.doi.org/10.1007/s11760-015-0817-x

Abstract

To contrive an accurate and efficient strategy for object detection–object track assignment problem, we present a tracklet clustering approach using distance dependent Chinese restaurant processes (ddCRPs), which employ a two-level robust object tracker. The first level is an ordinary tracklet generator that obtains short yet reliable tracklets. In the second level, we cluster the tracklets over time based on color, spatial and temporal attributes, where the nonparametric process of clustering with ddCRPs allows us to maintain an unknown number of objects. Unlike the previously proposed Chinese restaurant processes and Dirichlet process mixture models, our ddCRPs method does not require prescribed complex cluster models to be initialized and updated, and thus, we can cluster complex tracklets by only computing similarities between them. Our comparative evaluations on tracking different object types demonstrate the generality of our approach.

Item Type:Article
Uncontrolled Keywords:Distance dependent Chinese restaurant process; Tracklet clustering; Object tracking
Subjects:UNSPECIFIED
ID Code:27280
Deposited By:Hakan Erdoğan
Deposited On:27 Nov 2015 15:06
Last Modified:27 Nov 2015 15:06

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