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Locally Spatiotemporal Saliency Representation: The Role of Independent Component Analysis.

Authors :
Wang, Jun
Liao, Xiaofeng
Yi, Zhang
Jiang, Tao
Jiang, Xingzhou
Source :
Advances in Neural Networks - ISNN 2005 (9783540259121); 2005, p997-1003, 7p
Publication Year :
2005

Abstract

Locally spatiotemporal salience is defined as the combination of the local contrast salience from multiple paralleling independent spatiotemporal feature channels. The computational model proposed in this paper adopts independent component analysis (ICA) to model the spatiotemporal receptive filed of visual simple cells, then uses the learned independent filters for feature extraction. The ICA-based feature extraction for modelling locally spatiotemporal saliency representation (LSTSR) provides such benefits: (1) valid to use LSTSR directly for locally spatial saliency representation (LSSR) since it includes LSSR as one of its special case; (2) Plausible for space variant sampled dynamic scene; (3) Effective for motion-based scene segmentation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540259121
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2005 (9783540259121)
Publication Type :
Book
Accession number :
32862731
Full Text :
https://doi.org/10.1007/11427391_160