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Proceedings Paper

Multiple human detection and tracking by using multiple-stage HOG detector and PFGPDM
Author(s): Yafeng Yin; Hong Man; Sachi Desai; Haibo He
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Paper Abstract

Detection and tracking of a varying number of people is very essential in surveillance sensor systems. In the real applications, due to various human appearance and confusors, as well as various environmental conditions, multiple targets detection and tracking become even more challenging. In this paper, we proposed a new framework integrating a Multiple-Stage Histogram of Oriented Gradients (HOG) based human detector and the Particle Filter Gaussian Process Dynamical Model (PFGPDM) for multiple targets detection and tracking. The Multiple-Stage HOG human detector takes advantage from both the HOG feature set and the human motion cues. The detector enables the framework detecting new targets entering the scene as well as providing potential hypotheses for particle sampling in the PFGPDM. After processing the detection results, the motion of each new target is calculated and projected to the low dimensional latent space of the GPDM to find the most similar trained motion trajectory. In addition, the particle propagation of existing targets integrates both the motion trajectory prediction in the latent space of GPDM and the hypotheses detected by the HOG human detector. Experimental tests are conducted on the IDIAP data set. The test results demonstrate that the proposed approach can robustly detect and track a varying number of targets with reasonable run-time overhead and performance.

Paper Details

Date Published: 25 September 2009
PDF: 10 pages
Proc. SPIE 7480, Unmanned/Unattended Sensors and Sensor Networks VI, 74800S (25 September 2009); doi: 10.1117/12.834896
Show Author Affiliations
Yafeng Yin, Stevens Institute of Technology (United States)
Hong Man, Stevens Institute of Technology (United States)
Sachi Desai, U.S. Army Research, Development and Engineering Command (United States)
Haibo He, Stevens Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7480:
Unmanned/Unattended Sensors and Sensor Networks VI
Edward M. Carapezza, Editor(s)

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