Dropped object detection in crowded scenes
Name
526717739-MIT.pdf
Description
Full printable version
Size
12.76 MB
Format
Adobe PDF
Checksum (MD5)
ab940e9b8bfb8e7cc8216319e2e440fc
Author(s)
Bhatnagar, Deepti, S.M. Massachusetts Institute of Technology
Advisor(s)
W. Eric L. Grimson.
Date Issued
2009
Publisher
Massachusetts Institute of Technology
Abstract
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.
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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