Abstract
Computational visual attention modeling is a topic of increasing importance in machine understanding of images. In this paper, we present an approach to refine a region based attention model with eye tracking data. This paper has three main contributions. (1) A concept of fixation mask is proposed to describe the region saliency of an image by weighting the segmented regions using importance measures obtained in the Human Visual System (HVS) or computational models. (2) A Genetic Algorithm (GA) scheme for refining a region based attention model is proposed. (3) An evaluation method is developed to measure the correlation between the result from the computational model and that from the HVS in terms of fixation mask. Copyright © 2010 IEEE.
| Original language | English |
|---|---|
| Title of host publication | 2010 17th IEEE International Conference on Image Processing (ICIP 2010) |
| Place of Publication | Piscataway, NJ |
| Publisher | IEEE |
| Pages | 1105-1108 |
| Volume | 2 |
| ISBN (Electronic) | 9781424479948, 9781424479931 |
| ISBN (Print) | 9781424479924 |
| DOIs | |
| Publication status | Published - 2010 |
Citation
Liang, Z., Fu, H., Chi, Z., & Feng, D. (2010). Refining a region based attention model using eye tracking data. In 2010 17th IEEE International Conference on Image Processing (ICIP 2010) (Vol. 2, pp. 1105-1108). Piscataway, NJ: IEEE.Keywords
- Visual attention model
- Eye tracking data
- Genetic algorithm
- Fixation mask
- Regions of interest