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2000
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Visual Extraction of Motion-Based Information from Image Sequences

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Visual Extraction of Motion-Based Information from Image Sequences
We describe a system which is designed to assist in extracting high-level information from sets or sequences of images. We show that the method of principal components analysis followed by a neural network learning phase is capable of feature extraction or motion tracking, even through occlusion. Given a minimal amount of user direction for the learning phase, a wide range of features can be automatically extracted. Features discussed in this paper include information associated with human head motions and a birds wings during take off. We have quantified the results, for instance showing that with only 25 out of 424 frames of hand labelled information a system to track a persons nose can be trained almost as accurately as a human attempting the same task. We demonstrate a system that is powerful, flexible and, above all, easy for non-specialists to use.
David P. Gibson, Neill W. Campbell, Colin J. Dalto
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors David P. Gibson, Neill W. Campbell, Colin J. Dalton, Barry T. Thomas
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