NDLI: Automated Change Detection in an Undersea Environment using a Statistical Background Model

Content Provider	IEEE Xplore Digital Library
Author	Zhi Qi Cooperstock, J.R.
Copyright Year	2007
Description	Author affiliation: McGill Univ., Montreal (Zhi Qi; Cooperstock, J.R.)
Abstract	Marine scientists are turning increasingly to underwater video cameras in their research. These provide enormous quantities of visual data that often overwhelm the manual processing abilities of the scientists. To cope with such large data sets, an automated change detection system is proposed that helps isolate the time periods in which significant activity is found in the video sequence. Unlike change detection algorithms in use in terrestrial environments, the system must account for the photometric complexity of underwater video, including interference from small floating particles ("sea snow"), the scatter of light as it propagates through water, and the non-uniform frequency decay of light intensity with distance. In addition, certain activity, such as the motion of swimming fish that are attracted by the use of artificial lighting, is considered a distracter, and should, ideally, be ignored. These factors are addressed by our system, in large part through the use of Mixture-of-Gaussians background models.
Starting Page	1
Ending Page	6
File Size	3493870
Page Count	6
File Format	PDF
ISBN	9780933957350
DOI	10.1109/OCEANS.2007.4449201
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	MTS
Subject Keyword	Turning Cameras Video sequences Detection algorithms Photometry Interference Snow Light scattering Particle scattering Optical propagation
Content Type	Text
Resource Type	Article

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