An Object-Based Bayesian Framework for Top-Down Visual Attention

Proceedings of the 26th AAAI Conference on Artificial Intelligence, AAAI 2012

Volumn , Issue , 2012, Pages 1529-1535

  Borji, Ali ^a   Sihite, Dicky N ^a   Itti, Laurent ^b  

^a University of Southern California   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; BEHAVIORAL RESEARCH; CLASSIFICATION (OF INFORMATION); EYE MOVEMENTS; HUMAN COMPUTER INTERACTION; OBJECT DETECTION;

BAYESIAN FRAMEWORKS; BOTTOM-UP SALIENCIES; EYE FIXATIONS; EYE POSITION; OBJECT BASED; OBJECTS-BASED; PROBABILISTIC INFERENCE; STATE OF THE ART; TOP-DOWN VISUAL ATTENTIONS; TOPDOWN;

PROBABILITY DISTRIBUTIONS;

EID: 84898784456     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (40)

1. Ballard, D.; Hayhoe., M.; and Pelz., J. 1995. Memory representations in natural tasks. Journal of Cognitive Neuroscience 7(1).
2. Berg, D.; Boehnke, S.; Marino, R.; Munoz, D.; and Itti, L. 2009. Free viewing of dynamic stimuli by humans and monkeys. Journal of Vision 9(5):1-15.
3. Bian, P., and Zhang, L. 2009. Biological plausibility of spectral domain approach for spatiotemporal visual saliency. ICONIP'08.
4. BoostingToolbox. http://people.csail.mit.edu/torralba/shortcourserloc/boosting/boosting.
5. Bruce, N. D. B., and Tsotsos, J. K. 2005. Saliency based on information maximization. Neural Information Processing Systems.
6. Butko, N. J., and Movellan, J. R. 2009. Optimal scanning for faster object detection. CVPR.
7. Cagli, R. C.; Coraggio, P.; Napoletano, P.; Schwartz, O.; Ferraro, M.; and Boccignone, G. 2009. Visuomotor characterization of eye movements in a drawing task. Vision Research 49.
8. Einhauser, W.; Spain, M.; and Perona, P. 2008. Objects predict fixations better than early saliency. Journal of Vision. 8(14).
9. Erez, T.; Tramper, J.; Smart, B.; and Gielen, S. 2011. A pomdp model of eye-hand coordination. AAAI.
10. Felzenszwalb, P.; Girshick, R.; McAllester, D.; and Ramanan, D. 2010. Object detection with discriminatively trained part based models. IEEE Trans. PAMI. 32(9).
11. Garcia-Diaz, A.; Fdez-Vidal, X. R.; Pardo, X. M.; and Dosil, R. 2009. Decorrelation and distinctiveness provide with human-like saliency. Advanced Concepts for Intelligent Vision Systems (ACIVS). (5807).
12. Guo, C., and Zhang, L. 2010. A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Trans. on Image Processing. 19.
13. Harel, J.; Koch, C.; and Perona, P. 2006. Graph-based visual saliency. Neural Information Processing Systems. 19:545-552.
14. Hou, X., and Zhang, L. 2008. Dynamic visual attention: Searching for coding length increments. Neural Information Processing Systems.
15. Itti, L.; Koch, C.; and Niebur, E. 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. PAMI.
16. Judd, T.; Ehinger, K.; and Durand, F., a. T. A. 2009. Learning to predict where humans look. International Conference on Computer Vision (ICCV).
17. Land, M., and Hayhoe, M. 2001. In what ways do eye movements contribute to everyday activities? Vision Research 41(25).
18. Land, M. F., and Lee, D. N. 1994. Where we look when we steer. Nature 369:742-744.
19. Larochelle, H., and Hinton, G. E. 2010. Learning to combine foveal glimpses with a third-order boltzmann machine. NIPS.
20. LibSVM. http://www.csie.ntu.edu.tw/∼cjlin/libsvm/.
21. Mancas, M. 2007. Computational Attention: Modelisation and Application to Audio and Image Processing.
22. McCallum, A. K. 1995. Reinforcement Learning with Selective Perception and Hidden State.
23. Mennie, N.; Hayhoe, M.; and Sullivan, B. 2007. Look-ahead fixations: Anticipatory eye movements in natural tasks. Experimental Brain Research 179(3):427-442.
24. Najemnik, J., and Geisler, W. S. 2005. Optimal eye movement strategies in visual search. Nature. 434:387-391.
25. Navalpakkam, V., and Itti, L. 2005. Modeling the influence of task on attention. Vision Research 45:205-231.
26. Peters, R. J., and Itti, L. 2007. Beyond bottom-up: Incorporating task-dependent influences into a computational model of spatial attention. CVPR.
27. Peters, R.; Iyer, A.; Itti, L.; and Koch, C. 2005. Components of bottom-up gaze allocation in natural images. Vision Research 45(8).
28. Reichle, E. D.; Rayner, K.; and Pollatsek, A. 2003. The e-z reader model of eye movement control in reading: Comparisons to other models. Behavioral and Brain Sciences 26:445-476.
29. Renninger, L. W.; Coughlan, J. M.; Verghese, P.; and Malik, J. 2005. An information maximization model of eye movements. Neural Information Processing Systems (NIPS).
30. Rimey, R. D., and Brown, C. M. 1994. Control of selective perception using bayes nets and decision theory. International Journal of Computer Vision 12(2/3):173-207.
31. SaliencyToolbox. http://www.saliencytoolbox.net/.
32. Seo, H., and Milanfar, P. 2009. Static and space-time visual saliency detection by self-resemblance. Journal of Vision. 9(12).
33. Siagian, C., and Itti, L. 2007. Rapid biologically-inspired scene classification using features shared with visual attention. IEEE Trans. PAMI. 29(2):300-312.
34. Sprague, N., and Ballard, D. H. 2003. Eye movements for reward maximization. Neural Information Processing Systems (NIPS).
35. Tatler, B. W. 2007. The central fixation bias in scene viewing: Selecting an optimal viewing position independently of motor biases and image feature distributions. Journal of Vision. 14(7):1-17.
36. Toet, A. 2011. Computational versus psychophysical image saliency: a comparative evaluation study. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI). 33(11):2131-2146.
37. Torralba, A.; Oliva, A.; Castelhano, M.; and Henderson. 2006. Contextual guidance of attention in natural scenes: The role of global features on object search. Psychological Review.
38. Ullman, S. 1984. Visual routines. Cognition 18:97-159.
39. Yi, W., and Ballard, D. H. 2009. Recognizing behavior in hand-eye coordination patterns. International Journal of Humanoid Robotics.
40. Zhang, L.; Tong, M. H.; Marks, T. K.; Shan, H.; and Cottrell, G. W. 2008. Sun: A bayesian framework for saliency using natural statistics. Journal of Vision. 8(7).