A Computational Saliency Model Integrating Saccade Programming

Saliency models have showed the ability of predicting where human eyes fixate when looking at images. However, few models are interested in saccade programming strategies. We proposed a biologically-inspired model to compute image saliency maps. Based on these saliency maps, we compared three different saccade programming models 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 where the image is viewed at the highest resolution, 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.

[1]  J. Henderson.  Human gaze control during real-world scene perception , 2003, Trends in Cognitive Sciences.

[2]  Robert M. McPeek,et al.  Concurrent processing of saccades in visual search , 2000, Vision Research.

[3]  Derrick J. Parkhurst,et al.  Modeling the role of salience in the allocation of overt visual attention , 2002, Vision Research.

[4]  Wilson S. Geisler,et al.  Real-time foveated multiresolution system for low-bandwidth video communication , 1998, Electronic Imaging.

[5]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[6]  S. Yantis,et al.  Visual attention: control, representation, and time course. , 1997, Annual review of psychology.

[7]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[8]  Heiko Neumann,et al.  Recurrent Long-Range Interactions in Early Vision , 2001, Emergent Neural Computational Architectures Based on Neuroscience.

[9]  D. Navon.  Forest before trees: The precedence of global features in visual perception , 1977, Cognitive Psychology.

[10]  C. J. Erkelens,et al.  PII: S0042-6989(97)00287-3 , 2003 .

[11]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[12]  Jeanny Hérault,et al.  Realistic Simulation Tool for Early Visual Processing Including Space, Time and Colour Data , 1993, IWANN.

[13]  L. Itti.  Quantitative modelling of perceptual salience at human eye position , 2006 .

[14]  Antonio Torralba,et al.  Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. , 2006, Psychological review.