NDLI: Statistical shape theory for activity modeling

Content Provider	IEEE Xplore Digital Library
Author	Vaswani, N. Chowdhury, A.R. Chellappa, R.
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Maryland Univ., College Park, MD, USA (Vaswani, N.; Chowdhury, A.R.; Chellappa, R.)
Abstract	Monitoring activities in a certain region from video data is an important surveillance problem today. The goal is to learn the pattern of normal activities and detect unusual ones by identifying activities that deviate appreciably from the typical ones. In this paper we propose an approach using statistical shape theory (based on Kendall's shape model) [D.G. Kendall et al., 1999]. In a low resolution video each moving object is best represented as a moving point mass or particle. In this case, an activity can be defined by the interactions of all or some of these moving particles over time. We model this configuration of the particles by a polygonal shape formed from the locations of the points in a frame and the activity by the deformation of the polygons in time. These parameters are learnt for each typical activity. Given a test video sequence, an activity is classified as abnormal if the probability for the sequence (represented by the mean shape and the dynamics of the deviations), given the model is below a certain threshold. The approach gives very encouraging results in surveillance applications using a single camera and is able to identify various kinds of abnormal behaviors.
Sponsorship	IEEE Signal Process. Soc., Comput. Soc., Circuits & Syst. Soc, Commun. Soc
File Size	326775
File Format	PDF
ISBN	0780379659
DOI	10.1109/ICME.2003.1221278
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-07-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Active shape model Deformable models Video sequences Surveillance Cameras Image analysis Automation Educational institutions Computerized monitoring Object detection
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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