Dropped object detection in crowded scenes

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 83-85). === In the last decade, the topic of automated surveillance has become very important in the...

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Main Author: Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology
Other Authors: W. Eric L. Grimson.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2010
Subjects:
Online Access:http://hdl.handle.net/1721.1/53204
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-532042019-05-02T15:44:42Z Dropped object detection in crowded scenes Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology W. Eric L. Grimson. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. Cataloged from PDF version of thesis. Includes bibliographical references (p. 83-85). In the last decade, the topic of automated surveillance has become very important in the computer vision community. Especially important is the protection of critical transportation places and infrastructure like airport and railway stations. As a step in that direction, we consider the problem of detecting abandoned objects in a crowded scene. Assuming that the scene is being captured through a mid-field static camera, our approach consists of segmenting the foreground from the background and then using a change analyzer to detect any objects which meet certain criteria. In this thesis, we describe a background model and a method of bootstrapping that model in the presence of foreign objects in the foreground. We then use a Markov Random Field formulation to segment the foreground in image frames sampled periodically from the video camera. We use a change analyzer to detect foreground blobs that remain static through the scene and based on certain rules decide if the blob could be a potentially abandoned object. by Deepti Bhatnagar. S.M. 2010-03-25T15:14:23Z 2010-03-25T15:14:23Z 2009 2009 Thesis http://hdl.handle.net/1721.1/53204 526717739 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 85 p. application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Electrical Engineering and Computer Science.
spellingShingle Electrical Engineering and Computer Science.
Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology
Dropped object detection in crowded scenes
description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 83-85). === In the last decade, the topic of automated surveillance has become very important in the computer vision community. Especially important is the protection of critical transportation places and infrastructure like airport and railway stations. As a step in that direction, we consider the problem of detecting abandoned objects in a crowded scene. Assuming that the scene is being captured through a mid-field static camera, our approach consists of segmenting the foreground from the background and then using a change analyzer to detect any objects which meet certain criteria. In this thesis, we describe a background model and a method of bootstrapping that model in the presence of foreign objects in the foreground. We then use a Markov Random Field formulation to segment the foreground in image frames sampled periodically from the video camera. We use a change analyzer to detect foreground blobs that remain static through the scene and based on certain rules decide if the blob could be a potentially abandoned object. === by Deepti Bhatnagar. === S.M.
author2 W. Eric L. Grimson.
author_facet W. Eric L. Grimson.
Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology
author Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology
author_sort Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology
title Dropped object detection in crowded scenes
title_short Dropped object detection in crowded scenes
title_full Dropped object detection in crowded scenes
title_fullStr Dropped object detection in crowded scenes
title_full_unstemmed Dropped object detection in crowded scenes
title_sort dropped object detection in crowded scenes
publisher Massachusetts Institute of Technology
publishDate 2010
url http://hdl.handle.net/1721.1/53204
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