Scale adaptive visual attention detection by subspace analysis

Authors:
Yiqun Hu;Deepu Rajan;Liang-Tien Chia
Affiliations:
Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore
Venue:
Proceedings of the 15th international conference on Multimedia
Year:
2007

Citing 5
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Abstract

We describe a method to extract visual attention regions in images by robust subspace analysis from simple feature like intensity endowed with scale adaptivity in order to represent textured areas in an image. The scale adaptive descriptor is mapped onto clusters in linear spaces. A new subspace estimation algorithm based on the Generalized Principal Component Analysis (GPCA) is proposed to estimate multiple linear subspaces. The visual attention of each region is calculated using a new region attention measure that considers feature contrast and spatial geometric properties. Compared with existing visual attention detection methods, the proposed method directly measures global visual attention at the region level as opposed to pixel level.