Abstract
Saliency models provide a saliency map that is a topographically arranged map to represent the saliency of the visual scene. Saliency map is used to sequentially select particular locations of the scene to predict a subject’s eye scanpath when viewing the corresponding scene. A saliency map is most of the time computed using the same point of view or foveated point. Few models were interested in saccade programming strategies. In visual search tasks, studies shown that people can plan from one foveated point the next two saccades (and so, the next two fixations): this is called concurrent saccade programming. In this paper, we tested if such strategy occurs during natural scene free viewing. We tested different saccade programming strategies depending on the number of programmed saccades. The results showed that the strategy of programming one saccade at a time from the foveated point best matches the experimental data from free viewing of natural images. Because saccade programming models depend on the foveated point, we took into account the spatially variant retinal resolution. We showed that the predicted eye fixations were more effective when this retinal resolution was combined with the saccade programming strategies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Andrews, T.J., Coppola, D.M.: Idiosyncratic characteristics of saccadic eye movements when viewing different visual environments. Vision Research 39, 2947–2953 (1999)
Bahill, A.T., Adler, D., Stark, L.: Most naturally occurring human saccades have magnitudes of 15 degrees or less. Investigative Ophthalmology 14, 468–469 (1975)
Beaudot, W., Palagi, P., Herault, J.: Realistic simulation tool for early visual processing including space, time and colour data. In: Mira, J., Cabestany, J., Prieto, A.G. (eds.) IWANN 1993. LNCS, vol. 686, pp. 370–375. Springer, Heidelberg (1993)
Egeth, H.E., Yantis, S.: Visual attention: Control, representation, and time course. Annual Review of Psychology 48, 269–297 (1997)
Hansen, T., Sepp, W., Neumann, H.: Recurrent long-range interactions in early vision. In: Wermter, S., Austin, J., Willshaw, D.J. (eds.) Emergent Neural Computational Architectures Based on Neuroscience. LNCS (LNAI), vol. 2036, pp. 127–153. Springer, Heidelberg (2001)
Henderson, J.M.: Human gaze control in real-world scene perception. Trends in Cognitive Sciences 7, 498–504 (2003)
Itti, L.: Quantitative modeling of perceptual salience at human eye position. Visual Cognition 14, 959–984 (2006)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 1254–1259 (1998)
Koch, C., Ullman, S.: Shifts in selective visual attention: towards the underlying neural circuitry. Human Neurobiology 4, 219–227 (1985)
McPeek, R.M., Skavenski, A.A., Nakayama, K.: Adjustment of fixation duration in visual search. Vision Research 38, 1295–1302 (1998)
McPeek, R.M., Skavenski, A.A., Nakayama, K.: Concurrent processing of saccades in visual search. Vision Research 40, 2499–2516 (2000)
Navon, D.: Forest before trees: the precedence of global features in visual perception. Cognitive Psychology 9, 353–383 (1977)
Parkhurst, D., Law, K., Niebur, E.: Modeling the role of salience in the allocation of overt visual attention. Vision Research 42, 107–123 (2002)
Geisler, W.S., Perry, J.S.: A real-time foveated multiresolution system for low-bandwidth video communication. In: Human Vision and Electronic Imaging, Proceedings of SPIE, vol. 3299, pp. 294–305 (1998)
Perry, J.S.: http://fi.cvis.psy.utexas.edu/software.shtml
Torralba, A., Oliva, A., Castelhano, M.S., Henderson, J.M.: Contextual guidance of Eye Movements and Attention in Real-World Scenes: The Role of Global Features in Object Search. Psychological Review 113, 766–786 (2006)
Treisman, A., Gelade, G.: A feature integration theory of attention. Cognitive Psychology 12, 97–136 (1980)
Wandell, B.A.: Foundations of Vision. Stanford University (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ho-Phuoc, T., Guérin-Dugué, A., Guyader, N. (2010). A Biologically-Inspired Visual Saliency Model to Test Different Strategies of Saccade Programming. In: Fred, A., Filipe, J., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2009. Communications in Computer and Information Science, vol 52. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11721-3_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-11721-3_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11720-6
Online ISBN: 978-3-642-11721-3
eBook Packages: Computer ScienceComputer Science (R0)