NDLI: A multi-target tracking approach combined with occlusion segmentation

Content Provider	IEEE Xplore Digital Library
Author	Huan Ding Wensheng Zhang
Copyright Year	2011
Description	Author affiliation: State Key Laboratory of Intelligent Control and Management of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China (Huan Ding; Wensheng Zhang)
Abstract	Multiple-target tracking in complex scenes is one of the most complicated problems in computer vision. Handling the occlusion between objects is the key issue in multiple target tracking. This paper presents an occlusion segmentation-based method to track multiple people in complex situations which are captured by static monocular cameras. In the proposed method, we calculate the probabilistic histogram of each object's optical flow vector, then use this motion statistic information along with the color and appearance information to construct a new expression of pixel distance. Finally, a stepwise classification and K-means clustering method are taken advantages of to accomplish occlusion segmentation. Object tracking is handled by a particle filter-based tracking framework, and a probabilistic appearance model is used to find the best particle. Experiments are conducted using public challenging data set PETS 2009. Results show that our approach can improve the performance of the existing tracking approach and handle dynamic occlusions better.
Starting Page	150
Ending Page	156
File Size	358231
Page Count	7
File Format	PDF
ISBN	9781612843742
e-ISBN	9781612843759
DOI	10.1109/IWACI.2011.6159992
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical filters Computer vision Image motion analysis Histograms Target tracking Probabilistic logic Optical reflection
Content Type	Text
Resource Type	Article

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