NDLI: Spatio-temporal segmentation for video surveillance

Content Provider	IEEE Xplore Digital Library
Author	Hongzan Sun Tao Feng Tieniu Tan
Copyright Year	2000
Description	Author affiliation: Inst. of Autom., Acad. Sinica, Beijing, China (Hongzan Sun)
Abstract	Automatic extraction of moving objects and construction of site models are key problems in surveillance systems. We present an approach to segmenting moving objects from static scenes as well as building site models automatically. With the video sequence captured by a static camera, we describe a robust algorithm to estimate the background image as the 2D site environment map. Then, we can label each pixel in an image volume formed by a video sequence as either "foreground" or "background". Clustered foreground pixels are used as a cue to seed selection when we perform 3D segmentation in the image volume. Unlike some conventional segmentation approaches, our algorithm utilizes the spatio-temporal information instead of spatial information only. By a uniform 3D segmentation we can refine the estimate of the static environment map and detect the moving objects automatically. Experimental results on veal video sequences demonstrate the robustness and accuracy of the algorithm.
Starting Page	843
Ending Page	846
File Size	671837
Page Count	4
File Format	PDF
ISBN	0769507506
ISSN	10514651
DOI	10.1109/ICPR.2000.905544
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-09-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Video surveillance Image segmentation Video sequences Robustness Clustering algorithms Pixel Layout Buildings Cameras Object detection
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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