NDLI: Video segmentation for surveillance

Content Provider	IEEE Xplore Digital Library
Author	Juhua Zhu
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. Eng., Princeton Univ., NJ, USA (Juhua Zhu)
Abstract	Summary form only given. Video segmentation is usually termed as foreground (moving objects) segmentation in a fixed camera scenario, and as independent motion segmentation in a moving platform scenario. It is a fundamental step in many vision systems including video surveillance, human-machine interface, and very low-bandwidth telecommunications. Accurate foreground segmentation is a difficult task due to such factors as illumination variation, occlusion, background movements, and noise. We present a transform domain approach that employs a set of DCT-based features to exploit the spatial and temporal correlation in the video sequences. The approach is shown to be insensitive to illumination change and to noise. It also overcomes many common difficulties of segmentation such as foreground aperture, and moved background objects. The algorithm can perform in real-time. If time allows, I briefly show some results of the moving camera case. With a moving camera, estimation of camera ego-motion is the key issue. Our approach is based on solving an optimization problem for the FOE (focus of expansion). The flow field defined by FOE can be used to detect independent motions on the road.
File Size	130124
File Format	PDF
ISBN	0780390008
DOI	10.1109/WOCC.2005.1553764
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-04-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Motion segmentation Machine vision Video sequences Lighting Apertures Cameras Video surveillance Man machine systems Background noise
Content Type	Text
Resource Type	Article

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