2. Introduction
Saliency Map Models
Conclusions
文献リスト
文献紹介
[1] Itti, Koch, and Niebur, “A Model of Saliency-Based Visual Attention for Rapid
Scene Analysis,” PAMI, vol. 20, no. 11, 1998.
[2] Bruce and Tsotsos, “Saliency Based on Information Maximization,” NIPS, 2005.
[3] Harel, Koch, and Perona, “Graph-Based Visual Saliency,” NIPS, 2006.
[4] Hou and Zhang, “Saliency Detection : A Spectral Residual Approach,” CVPR,
2007.
[5] Zhang et al., “SUN: A Bayesian framework for saliency using natural statistics,”
Journal of Vision, vol. 8, no. 7, 2008.
[6] Garcia-Diaz et al., “Saliency from hierarchical adaptation through decorrelation
and variance normalization,” Image and Vision Computing, vol. 30, no. 1, 2012.
[7] Riche et al., “RARE2012: A multi-scale rarity-based saliency detection with its
comparative statistical analysis,” Signal Processing: Image Communication, vol. 28,
no. 6, 2013.
[8] Kummerer et al., “Deep Gaze I: Boosting Saliency Prediction with Feature Maps
Trained on ImageNet,” arXiv, 2014, 1411.1045v1.
2015/06/19 上智大学 山中高夫 Computational Models for Saliency Map
5. Introduction
Saliency Map Models
Conclusions
ITTI Model [Itti, PAMI1998] (1)
Architecture
1 Extraction of early visual features
2 Normalization of each visual feature
3 Integration of visual features
Early Visual Features
Intensity channels: 6 DoG
(Difference of Gaussian) images
Color channels: 6 DoG images × 2
color channels (RG, BY)
Orientation channels: 6 DoG
images × 4 orientations
(Gabor-filtered images)
2015/06/19 上智大学 山中高夫 Computational Models for Saliency Map