NDLI: Persistent Objects Tracking Across Multiple Non Overlapping Cameras

Content Provider	IEEE Xplore Digital Library
Author	Kang, Jinman Cohen, Isaac Medioni, Gerard
Copyright Year	2005
Description	Author affiliation: University of Southern California, Los Angeles (Kang, Jinman; Cohen, Isaac; Medioni, Gerard)
Abstract	We present an approach for persistent tracking of moving objects observed by non-overlapping and moving cameras. Our approach robustly recovers the geometry of non-overlapping views using a moving camera that pans across the scene. We address the tracking problem by modeling the appearance and motion of the moving regions. The appearance of the detected blobs is described by multiple spatial distributions models of blobs' colors and edges. This representation is invariant to 2D rigid and scale transformation. It provides a rich description of the detected regions, and produces an efficient blob similarity measure for tracking. The motion model is obtained using a Kalman Filter (KF) process, which predicts the position of the moving objects while taking into account the camera motion. Tracking is performed by the maximization of a joint probability model combining objects' appearance and motion. The novelty of our approach consists in defining a spatio-temporal Joint Probability Data Association Filter (JPDAF) for integrating multiple cues. The proposed method tracks a large number of moving people with partial and total occlusions and provides automatic handoff of tracked objects. We demonstrate the performance of the system on several real video surveillance sequences.
Starting Page	112
Ending Page	119
File Size	1227766
Page Count	8
File Format	PDF
ISBN	0769522718
DOI	10.1109/ACVMOT.2005.92
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-01-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Layout Monitoring Tracking Video surveillance Iris Computer vision Robustness Geometry Predictive models
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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