Name
Abstract | ||
|---|---|---|
A method for sensing human visual attention is proposed. The method is based on the analysis of sequential image patterns of faces and irises observed at regular time intervals. The basic concept is to represent the set of image patterns produced by the action of gazing at a certain area as a nonlinear subspace in a high-dimensional pattern vector space. Such a space is called an attention subspace. In this framework, an input subspace from an unknown action is classified into an attention subspace of gazing at a certain area or into attention subspaces of gazing at other areas (named non-attention subspaces) by measuring the canonical angles between the input subspace and pre-computed dictionary subspaces. To maintain performance even in the presence of head movement, two mechanisms are introduced: 1) the kernel orthogonal mutual subspace method, which is suitable for classifying sets of multiple images, and 2) a kernel function for considering the head position in addition to a kernel function for pixel values. The stable performance of the proposed method including situations with head movements is demonstrated through experiments. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICPR.2014.92 | ICPR |
Keywords | Field | DocType |
iris sequential image pattern analysis,pixel values,high-dimensional pattern vector space,gazing attention subspace classification,face recognition,face sequential image pattern analysis,multiple image classification,kernel orthogonal mutual subspace method,iris recognition,pre-computed dictionary subspaces,image classification,canonical angles,nonattention subspaces,human visual attention sensing,head position,regular time intervals,nonlinear subspace,sensing visual attention,head movement,kernel function,gazing action,image motion analysis | Kernel (linear algebra),Computer vision,Iris recognition,Vector space,Subspace topology,Pattern recognition,Visualization,Computer science,Linear subspace,Artificial intelligence,Pixel,Kernel (statistics) | Conference |
ISSN | Citations | PageRank |
1051-4651 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasuyuki Yamazaki | 1 | 0 | 0.34 |
| Hideitsu Hino | 2 | 99 | 25.73 |
| Kazuhiro Fukui | 3 | 828 | 71.55 |