Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
A Coherent Computational Approach to Model Bottom-Up Visual Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region-based visual attention analysis with its application in image browsing on small displays
Proceedings of the 15th international conference on Multimedia
what is the chance of happening: a new way to predict where people look
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
| Hi-index | 0.00 |
As a crucial step of the visual cognition and perception, visual attention analysis shows great importance in many research or application areas. In this paper, we treat this problem from a new angle, inspired by the classic gravitational field theory. By defining "mass" of each pixel, we compute "force" between them to obtain a so-called pseudo gravitational field over an image. Then, we propose an iteration algorithm to simulate the movement of the fixation points affected by this field. Finally, stable visual attention points or areas are obtained when those fixation points finally aggregate around some special pixels or areas. The main contributions are threefold: (1) by introducing classic gravitational field theory into visual attention analysis, a new point of view is proposed; (2) a competition scheme is constructed and the meaning of attraction can be applied into visual attention analysis intuitively; (3) by using pixels into computation through down sampling, a faster analysis method is achieved. The experimental result shows that our method is effective and consistent with the generally accepted definition of visual attention.