NDLI: Trajectory Analysis and Semantic Region Modeling Using Nonparametric Hierarchical Bayesian Models

Content Provider	Springer Nature Link
Author	Wang, Xiaogang Ma, Keng Teck Ng, Gee Wah Grimson, W. Eric L.
Copyright Year	2011
Abstract	We propose a novel framework of using a nonparametric Bayesian model, called Dual Hierarchical Dirichlet Processes (Dual-HDP) (Wang et al. in IEEE Trans. Pattern Anal. Mach. Intell. 31:539–555, 2009), for unsupervised trajectory analysis and semantic region modeling in surveillance settings. In our approach, trajectories are treated as documents and observations of an object on a trajectory are treated as words in a document. Trajectories are clustered into different activities. Abnormal trajectories are detected as samples with low likelihoods. The semantic regions, which are subsets of paths commonly taken by objects and are related to activities in the scene, are also modeled. Under Dual-HDP, both the number of activity categories and the number of semantic regions are automatically learnt from data. In this paper, we further extend Dual-HDP to a Dynamic Dual-HDP model which allows dynamic update of activity models and online detection of normal/abnormal activities. Experiments are evaluated on a simulated data set and two real data sets, which include 8,478 radar tracks collected from a maritime port and 40,453 visual tracks collected from a parking lot.
Starting Page	287
Ending Page	312
Page Count	26
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	95
Issue Number	3
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2011-05-28
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Visual surveillance Activity analysis Trajectory analysis Scene modeling Abnormality detection Nonparametric hierarchical Bayesian models Clustering Gibbs sampling Image Processing and Computer Vision Pattern Recognition Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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