Graph cut video object segmentation using histogram of oriented gradients

This paper introduces a novel way to implement Graph Cut for video object segmentation with shape information. Graph Cut is a very efficient algorithm for image segmentation and Histogram of Oriented Gradients (HOG) is useful in detecting humans. We combine the HOG feature to incorporate a shape pri...

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Bibliographic Details
Published in2008 IEEE International Symposium on Circuits and Systems pp. 2590 - 2593
Main Authors Wang, Chun-Hao, Guan, Ling
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.01.2008
Subjects
Costs
Histograms
Humans
Image segmentation
MPEG 4 Standard
Object segmentation
Shape
Topology
Tracking
Video compression
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Summary:This paper introduces a novel way to implement Graph Cut for video object segmentation with shape information. Graph Cut is a very efficient algorithm for image segmentation and Histogram of Oriented Gradients (HOG) is useful in detecting humans. We combine the HOG feature to incorporate a shape prior into Graph Cut algorithm as a new way to enhance video object segmentation accuracy. In previous work, we used a fully connected 3-D that is slow and is subject to weak edges, inconsistent luminance. The new method is compared with old methods to show that it helps by introducing a shape prior for segmentation of pre-trained objects such as humans.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISBN:9781424416837
1424416833
ISSN:0271-4302
DOI:10.1109/ISCAS.2008.4541986