NDLI: Tracking appearances with occlusions

Content Provider	IEEE Xplore Digital Library
Author	Ying Wu Ting Yu Gang Hua
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Northwestern Univ., Evanston, IL, USA (Ying Wu; Ting Yu; Gang Hua)
Abstract	Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during tracking. To cope with the occlusion problem explicitly, this paper proposes a dynamic Bayesian network, which accommodates an extra hidden process for occlusion and stipulates the conditions on which the image observation likelihood is calculated. The statistical inference of such a hidden process can reveal the occlusion relations among different targets, which makes the tracker more robust against partial even complete occlusions. In addition, considering the fact that target appearances change with views, another generative model for multiple view representation is proposed by adding a switching variable to select from different view templates. The integration of the occlusion model and multiple view model results in a complex dynamic Bayesian network, where extra hidden processes describe the switch of targets' templates, the targets' dynamics, and the occlusions among different targets. The tracking and inferring algorithms are implemented by the sampling-based sequential Monte Carlo strategies. Our experiments show the effectiveness of the proposed probabilistic models and the algorithms.
Sponsorship	IEEE Comput. Soc Tech. Committee on Pattern Anal. & Machine Intelligence (TCPAMI)
File Size	505149
File Format	PDF
ISBN	0769519008
ISSN	10636919
DOI	10.1109/CVPR.2003.1211433
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-06-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target tracking Bayesian methods Hidden Markov models Switches Monte Carlo methods Inference algorithms Maintenance engineering Robustness Application software Human computer interaction
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
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
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Weighted Bayesian Network for Visual Tracking

Generative Graphical Models for Maneuvering Object Tracking and Dynamics Analysis

Switching observation models for contour tracking in clutter

MRF augmented particle filter tracker

Collaborative tracking of multiple targets

Coupled hidden Markov models for complex action recognition

Recognizing mobile organizations from column formations using hierarchical hidden Markov models: a simulation experiment

A new Bayesian framework for object recognition

Visual tracking using high-order Monte Carlo Markov chain

Tracking appearances with occlusions

Similar Documents

Weighted Bayesian Network for Visual Tracking

Generative Graphical Models for Maneuvering Object Tracking and Dynamics Analysis

Switching observation models for contour tracking in clutter

MRF augmented particle filter tracker

Collaborative tracking of multiple targets

Coupled hidden Markov models for complex action recognition

Recognizing mobile organizations from column formations using hierarchical hidden Markov models: a simulation experiment

A new Bayesian framework for object recognition

Visual tracking using high-order Monte Carlo Markov chain

Tracking appearances with occlusions