NDLI: Probabilistic framework for segmenting people under occlusion

Content Provider	IEEE Xplore Digital Library
Author	Elgammal, A.E. Davis, L.S.
Copyright Year	2001
Description	Author affiliation: Comput. Vision Lab., Maryland Univ., College Park, MD, USA (Elgammal, A.E.)
Abstract	In this paper we address the problem of segmenting foreground regions corresponding to a group of people given models of their appearance that were initialized before occlusion. We present a general framework that uses maximum likelihood estimation to estimate the best arrangement for people in terms of 2D translation that yields a segmentation for the foreground region. Given the segmentation result we conduct occlusion reasoning to recover relative depth information and we show how to utilize this depth information in the same segmentation framework. We also present a more practical solution for the segmentation problem that is online to avoid searching an exponential space of hypothesis. The person model is based on segmenting the body into regions in order to spatially localize the color-features corresponding to the way people are dressed. Modeling these regions involves modeling their appearance (color distributions) as well us their spatial distribution with respect to the body. We use a non-parametric approach bused on kernel density estimation to represent the color distribution of each region and therefore we do not restrict the clothing to be of uniform color instead it can be any mixture of colors and/or patterns. We also present a method to automatically initialize these models and learn them before the occlusion.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Anal. & Machine Intelligence
Starting Page	145
Ending Page	152
File Size	919429
Page Count	8
File Format	PDF
ISBN	0769511430
DOI	10.1109/ICCV.2001.937617
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Surveillance Target tracking Yield estimation Kernel Layout Clothing Computer vision Laboratories Educational institutions Indexing
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
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
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