Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72067
Title: Tracking multiple objects using probability hypothesis density filter and color measurements
Authors: Nam, T.P.
Weimin, H.
Ong, S.H. 
Issue Date: 2007
Source: Nam, T.P.,Weimin, H.,Ong, S.H. (2007). Tracking multiple objects using probability hypothesis density filter and color measurements. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007 : 1511-1514. ScholarBank@NUS Repository.
Abstract: Most methods for multiple object tracking in video represent the state of multi-object in a high dimensional joint state space. This leads to high computational complexity. This paper presents a method using the probability hypothesis density (PHD) filter to estimate the state of multiple objects in video. The method operates on the single object state space instead of the joint state space. A PHD recursion for visual observations with color measurements is proposed. Our method can track varying number of objects. © 2007 IEEE.
Source Title: Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
URI: http://scholarbank.nus.edu.sg/handle/10635/72067
ISBN: 1424410177
Appears in Collections:Staff Publications

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