Apply GPCA to motion segmentation

This source preferred by Hongchuan Yu and Jian Jun Zhang

Authors: Yu, H.

Editors: Zhang, J.J., Shao, L., Zhang, L. and Jones, G.A.

http://eprints.bournemouth.ac.uk/16652/

Pages: 21-38

Publisher: Springer-Verlag

ISBN: 9783642175534

DOI: 10.1007/978-3-642-17554-1

In this paper, we present a motion segmentation approach based on the subspace segmentation technique, the generalized PCA. By incorporating the cues from the neighborhood of intensity edges of images, motion segmentation is solved under an algebra framework. Our main contribution is to propose a post-processing procedure, which can detect the boundaries of motion layers and further determine the layer ordering. Test results on real imagery have confirmed the validity of our method.

This data was imported from DBLP:

Authors: Yu, H. and Zhang, J.-J.

http://eprints.bournemouth.ac.uk/16652/

Volume: 3

Pages: 45-54

This data was imported from Scopus:

Authors: Yu, H. and Zhang, J.J.

http://eprints.bournemouth.ac.uk/16652/

Volume: 332

Pages: 21-38

ISBN: 9783642175534

DOI: 10.1007/978-3-642-17554-1_2

In this paper, we present a motion segmentation approach based on the subspace segmentation technique, the generalized PCA. By incorporating the cues from the neighborhood of intensity edges of images, motion segmentation is solved under an algebra framework. Our main contribution is to propose a post-processing procedure, which can detect the boundaries of motion layers and further determine the layer ordering. Test results on real imagery have confirmed the validity of our method. © 2011 Springer-Verlag Berlin Heidelberg.

The data on this page was last updated at 04:50 on December 17, 2018.