Methods for comparing scanpaths and saliency maps: Strengths and weaknesses

Behavior Research Methods

Volumn 45, Issue 1, 2013, Pages 251-266

  Le Meur, Olivier ^a   Baccino, Thierry ^b  

^a UNIVERSITÉ DE RENNES 1   (France)

^b UNIVERSITÉ PARIS 8   (France)

Author keywords

Eye movement; Saliency; Visual attention

Indexed keywords

ALGORITHM; ARTICLE; ATTENTION; BIOLOGICAL MODEL; CLASSIFICATION; COMPARATIVE STUDY; DIFFERENTIAL THRESHOLD; EYE MOVEMENT; HUMAN; OCULOGRAPHY; OPTIC FLOW; PATTERN RECOGNITION; PERIMETRY; RECEIVER OPERATING CHARACTERISTIC; VISUAL FIELD;

ALGORITHMS; ATTENTION; DIFFERENTIAL THRESHOLD; EYE MOVEMENT MEASUREMENTS; EYE MOVEMENTS; HUMANS; MODELS, BIOLOGICAL; OPTIC FLOW; PATTERN RECOGNITION, VISUAL; ROC CURVE; VISUAL FIELD TESTS; VISUAL FIELDS;

EID: 84874351786     PISSN: 1554351X     EISSN: 15543528     Source Type: Journal    
DOI: 10.3758/s13428-012-0226-9     Document Type: Article

References (58)

1. Althoff, R. R., & Cohen, N. J. (1999). Eye-movement-based memory effect: A reprocessing effect in face perception. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 997-1010.
2. Antes, J. R. (1974). The time course of picture viewing. Journal of Experimental Psychology, 103, 62-70.
3. Baccino, T. (2004). La Lecture électronique [Digital Reading]. Grenoble: Presses Universitaires de Grenoble, Coll. Sciences et Technologies de la Connaissance.
4. Baccino, T. (2011). Eye movements and concurrent ERP's: EFRPs investigations in reading. In S. Liversedge, I. D. Gilchrist, & S. Everling (Eds.), Handbook on eye movements (pp. 857-870). Oxford: Oxford University Press.
5. Baccino, T., & Manunta, Y. (2005). Eye-fixation-related potentials: Insight into parafoveal processing. Journal of Psychophysiology, 19, 204-215.
6. Bindemann, M. (2010). Scene and screen center bias early eye movements in scene viewing. Vision Research, 50, 2577-2587.
7. Bruce, N. D. B., & Tsotsos, J. K. (2006). Saliency based on information maximisation. Advances in Neural Information Processing System, 18, 155-162.
8. Bruce, N. D. B., & Tsotsos, J. K. (2009). Saliency, attention, and visual search: An information theoretic approach. Journal of Vision, 9(3), 1-24.
9. Chanceaux, M., Guérin-Dugué, A., Lemaire, B., & Baccino, T. (2009). Towards a model of information seeking by integrating visual, semantic and memory maps. In B. Caputo & M. Vincze (Eds.), ICVW 2008 (pp. 65-78). Heidelberg: Springer.
10. Delorme, A., Richard, G., & Fabre-Thorpe, M. (2010). Key visual features for rapid categorization of animals in natural scenes. Frontiers in Psychology, 1, 21.
11. Efron, B., & Tibshirani, R. (1993). An introduction to the bootstrap. New York: Chapman and Hall.
12. Einhauser, W., & Konig, P. (2003). Does luminance-contrast contribute to a saliency for overt visual attention? European Journal of Neuroscience, 17, 1089-1097.
13. Follet, B., Le Meur, O., & Baccino, T. (2011). New insights into ambient and focal visual fixations using an automatic classification algorithm. I-Perception, 2, 592-610.
14. Green, D., & Swets, J. (1966). Signal detection theory and psychophysics. New York: Wiley.
15. Henderson, J. M. (2007). Regarding scenes. Current Directions in Psychological Science, 16, 219-222.
16. Irwin, D. E., & Zelinsky, G. J. (2002). Eye movements and scene perception: Memory for things observed. Perception & Psychophysics, 64, 882-895.
17. Itti, L. (2005). Quantifying the contribution of low-level saliency to human eye movements in dynamic scenes. Visual Cognition, 12, 1093-1123.
18. Itti, L., & Baldi, P. (2009). Bayesian surprise attracts human attention. Vision Research, 49, 1295-1306.
19. Itti, L., Koch, C., & Niebur, E. (1998). A model for saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20, 1254-1259.
20. Jarodzka, H., Holmqvist, K., & Nystr, M. (2010). A vector-based, multidimensional scanpath similarity measure. In C. Morimoto & H. Instance (Eds.), Proceedings of the 2010 symposium on eye tracking research and applications (pp. 211-218). New York: ACM.
21. Josephson, S., & Holmes, M. E. (2002). Attention to repeated images on the World-Wide Web: Another look at scanpath theory. Behavior Research Methods, Instruments, & Computers, 34, 539-548.
22. Jost, T., Ouerhani, N., von Wartburg, R., Mauri, R., & Haugli, H. (2005). Assessing the contribution of color in visual attention. Computer Vision and Image Understanding, 100, 107-123.
23. Judd, T., Ehinger, K., Durand, F., & Torralba, A. (2009). Learning to predict where humans look. Paper presented at the IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan.
24. Just, M. A., & Carpenter, P. A. (1976). Eye fixations and cognitive processes. Cognitive Psychology, 8, 441-480.
25. Le Meur, O., Baccino, T., & Roumy, A. (2011). Prediction of the inter-observer visual congruency (IOVC) and application to image ranking. In Proceedings of ACM Multimedia (pp. 373-382). Scottsdale, Arizona.
26. Le Meur, O., & Le Callet, P. (2009). What we see is most likely to be what matters: Visual attention and applications. In Proceedings of International Conference on Image Processing (pp. 3085-3088). Cairo, Egypt.
27. Le Meur, O., Le Callet, P., Barba, D., & Thoreau, D. (2006). A coherent computational approach to model bottom-up visual attention. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 802-817.
28. Lemaire, B., Guérin-Dugué, A., Baccino, T., Chanceaux, M., & Pasqualotti, L. (2011). A cognitive computational model of eye movements investigating visual strategies on textual material, In Proceedings of the Annual Conference of the Cognitive Science Society (pp. 1146-1151). Boston, MA.
29. Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics - Doklady, 6, 707-710.
30. Mannan, S. K., Ruddock, K. H., & Wooding, D. S. (1995). Automatic control of saccadic eye movements made in visual inspection of briefly presented 2-D images. Spatial Vision, 9, 363-386.
31. Mannan, S. K., Ruddock, K. H., & Wooding, D. S. (1996). The relationship between the locations of spatial features and those of fixations made during visual examination of briefly presented images. Spatial Vision, 10, 165-188.
32. Mannan, S. K., Ruddock, K. H., & Wooding, D. S. (1997). Fixation sequences made during visual examination of briefly presented 2D images. Spatial Vision, 11, 157-178.
33. Nisbett, R. (2003). The geography of thought: How Asians and Westerners think differently and why. New York: Free Press.
34. Over, E. A. B., Hooge, I. T. C., Vlaskamp, B. N. S., & Erkelens, C. J. (2007). Coarse-to-fine eye movement strategy in visual search. Vision Research, 47, 2272-2280.
35. Pannasch, S., Schulz, J., & Velichkovsky, B. M. (2011). On the control of visual fixation durations in free viewing of complex images. Attention, Perception, & Psychophysics, 73, 1120-1132.
36. Peters, R. J., & Itti, L. (2008). Applying computational tools to predict gaze direction in interactive visual environments. ACM Transactions on Applied Perception, 5, 1-21.
37. Peters, R. J., Iyer, A., Itti, L., & Koch, C. (2005). Components of bottom-up gaze allocation in natural images. Vision Research, 45, 2397-2416.
38. Privitera, C. M., & Stark, L. W. (2000). Algorithms for defining visual regions-of-interest: Comparison with eye fixations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 970-982.
39. Rajashekar, U., van der Linde, I., Bovik, A. C., & Cormack, L. K. (2008). Gaffe: A gaze-attentive fixation finding engine. IEEE Transactions on Image Processing, 17, 564-573.
40. Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124, 372-422.
41. Rayner, K., Castelhano, M. S., & Yang, J. (2009). Eye movements when looking at unusual-weird scenes: Are there cultural differences? Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 154-259.
42. Renninger, L. W., Verghese, P., & Coughlan, J. (2007). Where to look next? Eye movements reduce local uncertainty. Journal of Vision, 7(3, Art. 6), 1-17.
43. Rousselet, G. A., Macé, J. M., & Fabre-Thorpe, M. (2003). Is it an animal? Is it a human face? Fast processing in upright and inverted natural scenes. Journal of Vision, 3(6), 440-456.
44. Simola, J., Salojärvi, J., & Kojo, I. (2008). Using hidden Markov model to uncover processing states from eye movements in information search tasks. Cognitive Systems Research, 9, 237-251.
45. 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, 7(14, Art. 4), 1-17. doi: 10. 1167/7. 14. 4.
46. Tatler, B. W., Baddeley, R. J., & Gilchrist, I. D. (2005). Visual correlates of fixation selection: Effects of scale and time. Vision Research, 45, 643-659.
47. Tatler, B. W., & Vincent, B. T. (2008). Systematic tendencies in scene viewing. Journal of Eye Movement Research, 2(2), 1-18.
48. Toet, A. (2011). Computational versus psychophysical bottom-up image saliency: A comparative evaluation study. IEEE Trans. on Pattern Analysis and Machine Intelligence, 33, 2131-2146.
49. Torralba, A., Oliva, A., Castelhano, M. S., & Henderson, J. M. (2006). Contextual guidance of eye movements and attention in real-world scenes: The role of global features in object search. Psychological Review, 113, 766-786.
50. Trevarthen, C. B. (1968). Two mechanisms of vision in primates. Psychologische Forschung, 31, 299-337.
51. Unema, P. J. A., Pannasch, S., Joos, M., & Velichkovsky, B. M. (2005). Time course of information processing during scene perception: The relationship between saccade amplitude and fixation duration. Visual Cognition, 12, 473-494.
52. Velichkovsky, B. M. (2002). Heterarchy of cognition: The depths and the highs of a framework for memory research. Memory, 10, 405-419.
53. Velichkovsky, B. M., Pomplum, M., Rieser, J., & Ritter, H. J. (1996). Attention and communication: Eye-movement-based research paradigms. Visual attention and cognition. Amsterdam: Elsevier.
54. Viviani, P. (1990). Eye movements in visual search: Cognitive, perceptual and motor control aspects. Reviews of Oculomotor Research, 4, 353-393.
55. Wagner, R. A., & Fischer, M. J. (1974). The string-to-string correction problem. Journal of the ACM, 21, 168-173.
56. Yarbus, A. (1967). Eye movements and vision. New York: Plenum.
57. Zhang, L., Tong, M. H., Marks, T. K., Shan, H., & Cottrell, G. W. (2008). Sun: A Bayesian framework for salience using natural statistics. Journal of Vision, 8(7, Art. 32), 1-20.
58. Zhao, Q., & Koch, C. (2011). Learning a saliency map using fixated locations in natural scenes. Journal of Vision, 11(3, Art. 9), 1-15.