A Time-Dependent Saliency Model Combining Center and Depth Biases for 2D and 3D Viewing Conditions

Cognitive Computation

Volumn 4, Issue 2, 2012, Pages 141-156

  Gautier, J ^a   Le Meur, O ^a  

^a UNIVERSITÉ DE RENNES 1   (France)

Author keywords

Binocular disparity; Eye movements; Saliency model; Stereoscopy

Indexed keywords

3D VIEWING; BEHAVIORAL ANALYSIS; BINOCULAR DISPARITY; BOTTOM-UP ATTENTION; COMPUTATIONAL MODEL; DEPTH INFORMATION; EYE-TRACKING; FOREGROUND FEATURES; FOREGROUND/BACKGROUND; LOW-LEVEL FEATURES; NATURAL IMAGES; SALIENT REGIONS; STEREOSCOPY; TIME-DEPENDENT; VIEWING CONDITIONS; VISUAL ATTENTION; VISUAL EXPLORATION; VISUAL FEATURE;

BINOCULARS; EYE MOVEMENTS; FORECASTING;

THREE DIMENSIONAL;

EID: 84862123214     PISSN: 18669956     EISSN: 18669964     Source Type: Journal    
DOI: 10.1007/s12559-012-9138-3     Document Type: Article

References (35)

1. Koch C, Ullman S. Shifts in selective visual attention: towards the underlying neural circuitry. Hum Neurobiol. 1985; 4(4): 219-27.
2. Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell. 1998; 20(11): 1254-9.
3. Yarbus AL. Eye movements and vision. New York: Plenum press; 1967.
4. Torralba A, Oliva A, Castelhano MS, Henderson JM. Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. Psychol Rev. 2006; 113(4): 766-86.
5. Cutting JE, Vishton PM. Perceiving layout and knowing distances: the integration, relative potency, and contextual use of different information about depth. Percept Space Motion. 1995; 5: 69-117.
6. Maki A, Nordlund P, Eklundh JO. A computational model of depth-based attention. In: Proceedings of the 13th international conference on pattern recognition; 1996. p. 734-739.
7. Maki A, Nordlund P, Eklundh JO. Attentional scene segmentation: integrating depth and motion. Comput Vis Image Underst. 2000; 78(3): 351-73.
8. Ouerhani N, Hugli H. Computing visual attention from scene depth. In: Proceedings of 15th international conference on pattern recognition; 2000. p. 375-378.
9. Zhang Y, Jiang G, Yu M, Chen K. Stereoscopic visual attention model for 3D video. Adv Multimed Model. 2010; 5916: 314-24.
10. Bruce NDB, Tsotsos JK. An attentional framework for stereo vision. In: Proceedings of the 2nd Canadian conference on computer and robot vision; 2005. p. 88-95.
11. Tatler BW. The central fixation bias in scene viewing: selecting an optimal viewing position independently of motor biases and image feature distributions. J Vis. 2007; 7(14): 1-17.
12. Judd T, Ehinger K, Durand F, Torralba A. Learning to predict where humans look. IEEE 12th international conference on computer vision. 2009. p. 2106-2113.
13. Zhao Q, Koch C. Learning a saliency map using fixated locations in natural scenes. J Vis. 2011; 11(3): 1-15.
14. Vincent BT, Baddeley R, Correani A, Troscianko T, Leonards U. Do we look at lights? Using mixture modelling to distinguish between low-and high-level factors in natural image viewing. Vis Cognit. 2009; 17(6): 856-79.
15. Ho-Phuoc T, Guyader N, Guerin-Dugue A. A functional and statistical bottom-up saliency model to reveal the relative contributions of low-level visual guiding factors. Cogn Comput. 2010; 2(4): 344-59.
16. Jansen L, Onat S, König P. Influence of disparity on fixation and saccades in free viewing of natural scenes. J Vis. 2009; 11(5): 1-23.
17. Steger JM, König P. Fusion of 3D laser scans and stereo images for disparity maps of natural scenes. Osnabruck: Institute of Cognitive Science; 2010.
18. Le Meur O, Baccino T, Roumy A, et al. Prediction of the inter-observer visual congruency (IOVC) and application to image ranking. In: Proceedings of the 19th ACM international conference on Multimedia; 2011. p. 373-82.
19. Bindemann M. Scene and screen center bias early eye movements in scene viewing. Vis Res. 2010; 50(23): 2577-87.
20. Bruce ND. Features that draw visual attention: an information theoretic perspective. Neurocomputing. 2005; 65: 125-33.
21. Le Meur O, Le Callet P, Barba D, Thoreau D. A coherent computational approach to model bottom-up visual attention. IEEE Trans Pattern Anal Mach Intell. 2006; 28(5): 802-17.
22. Zhaoping L, Guyader N, Lewis A. Relative contributions of 2D and 3D cues in a texture segmentation task, implications for the roles of striate and extrastriate cortex in attentional selection. J Vis. 2009; 9(11): 1-22.
23. Parkhurst D, Law K, Niebur E. Modeling the role of salience in the allocation of overt visual attention. Vis Res. 2002; 42(1): 107-23.
24. Tatler BW, Baddeley RJ, Gilchrist ID. Visual correlates of fixation selection: effects of scale and time. Vis Res. 2005; 45(5): 643-59.
25. Underwood G. Cognitive processes in eye guidance: algorithms for attention in image processing. Cogn Comput. 2009; 1(1): 64-76.
26. Cutsuridis V. A cognitive model of saliency, attention, and picture scanning. Cogn Comput. 2009; 1(4): 292-9.
27. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc. 1977; 39: 1-38.
28. Rubin E. Visuell wahrgenommene figuren: studien in psychologischer analyse. Gyldendalske boghandel; 1921.
29. Palmer S. Vision: from photons to phenomenology. Cambridge: MIT Press; 2000.
30. Qiu FT, Sugihara T, von der Heydt R. Figure-ground mechanisms provide structure for selective attention. Nat Neurosci. 2007; 10(11): 1492-9.
31. Peters RJ, Itti L. Beyond bottom-up: incorporating task-dependent influences into a computational model of spatial attention. IEEE conference on computer vision and pattern recognition; 2007. p. 1-8.
32. Jost T, Ouerhani N, Wartburg R, Müri R, Hügli H. Assessing the contribution of color in visual attention. Comput Vis Image Underst. 2005; 100(1-2): 107-23.
33. Le Meur O, Chevet JC. Relevance of a feed-forward model of visual attention for goal-oriented and free-viewing tasks. IEEE Trans Image Process. 2010; 19(11): 2801-13.
34. VanRullen R. Visual saliency and spike timing in the ventral visual pathway. J Physiol Paris. 2003; 97(2-3): 365-77.
35. Chamaret C, Chevet JC, Le Meur O. Spatio-temporal combination of saliency maps and eye-tracking assessment of different strategies. 17th IEEE international conference on image processing (ICIP); 2010. p. 1077-1080.