The central fixation bias in scene viewing: selecting an optimal viewing position independently of motor biases and image feature distributions.

Observers show a marked tendency to fixate the center of the screen when viewing scenes on computer monitors. This is often assumed to arise because image features tend to be biased toward the center of natural images and fixations are correlated with image features. A common alternative explanation is that experiments typically use a central pre-trial fixation marker, and observers tend to make small amplitude saccades. In the present study, the central bias was explored by dividing images post hoc according to biases in their image feature distributions. Central biases could not be explained by motor biases for making small saccades and were found irrespective of the distribution of image features. When the scene appeared, the initial response was to orient to the center of the screen. Following this, fixation distributions did not vary with image feature distributions when freely viewing scenes. When searching the scenes, fixation distributions shifted slightly toward the distribution of features in the image, primarily during the first few fixations after the initial orienting response. The endurance of the central fixation bias irrespective of the distribution of image features, or the observer's task, implies one of three possible explanations: First, the center of the screen may be an optimal location for early information processing of the scene. Second, it may simply be that the center of the screen is a convenient location from which to start oculomotor exploration of the scene. Third, it may be that the central bias reflects a tendency to re-center the eye in its orbit.

[1]  L. Stark,et al.  Most naturally occurring human saccades have magnitudes of 15 degrees or less. , 1975, Investigative ophthalmology.

[2]  J. Pelz,et al.  Oculomotor behavior and perceptual strategies in complex tasks , 2001, Vision Research.

[3]  D. F. Fisher,et al.  Eye movements : cognition and visual perception , 1982 .

[4]  Michael L. Mack,et al.  Human Gaze Control in RealWorld Search , 2004, WAPCV.

[5]  Derrick J. Parkhurst,et al.  Scene content selected by active vision. , 2003, Spatial vision.

[6]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[7]  A. L. I︠A︡rbus Eye Movements and Vision , 1967 .

[8]  Preeti Verghese,et al.  Where to look next? Eye movements reduce local uncertainty. , 2007, Journal of vision.

[9]  M. Kenward,et al.  An Introduction to the Bootstrap , 2007 .

[10]  P Reinagel,et al.  Natural scene statistics at the centre of gaze. , 1999, Network.

[11]  John K. Tsotsos,et al.  Attention and Performance in Computational Vision , 2008 .

[12]  Jitendra Malik,et al.  An Information Maximization Model of Eye Movements , 2004, NIPS.

[13]  Daniela Zambarbieri,et al.  Saccade latency toward auditory targets depends on the relative position of the sound source with respect to the eyes , 1995, Vision Research.

[14]  J. Fuller,et al.  Eye position and target amplitude effects on human visual saccadic latencies , 1996, Experimental Brain Research.

[15]  Derrick J. Parkhurst,et al.  Texture contrast attracts overt visual attention in natural scenes , 2004, The European journal of neuroscience.

[16]  D. S. Wooding,et al.  Automatic control of saccadic eye movements made in visual inspection of briefly presented 2-D images. , 1995, Spatial vision.

[17]  D. S. Wooding,et al.  Fixation sequences made during visual examination of briefly presented 2D images. , 1997, Spatial vision.

[18]  T. Foulsham,et al.  Eye movements during scene inspection: A test of the saliency map hypothesis , 2006 .

[19]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[20]  L. Itti,et al.  Visual causes versus correlates of attentional selection in dynamic scenes , 2006, Vision Research.

[21]  M. Hayhoe,et al.  In what ways do eye movements contribute to everyday activities? , 2001, Vision Research.

[22]  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.

[23]  R. Baddeley,et al.  The long and the short of it: Spatial statistics at fixation vary with saccade amplitude and task , 2006, Vision Research.

[24]  D. S. Wooding,et al.  The relationship between the locations of spatial features and those of fixations made during visual examination of briefly presented images. , 1996, Spatial vision.

[25]  F. Vitu,et al.  Eye movements in reading isolated words: evidence for strong biases towards the center of the screen , 2004, Vision Research.

[26]  Wilson S. Geisler,et al.  Optimal eye movement strategies in visual search , 2005, Nature.

[27]  Michael Brady,et al.  Saliency, Scale and Image Description , 2001, International Journal of Computer Vision.

[28]  Alan C Bovik,et al.  Contrast statistics for foveated visual systems: fixation selection by minimizing contrast entropy. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[29]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[30]  P. König,et al.  Does luminance‐contrast contribute to a saliency map for overt visual attention? , 2003, The European journal of neuroscience.

[31]  T. Foulsham,et al.  Quarterly Journal of Experimental Psychology: in press Visual saliency and semantic incongruency influence eye movements when , 2022 .

[32]  H. Intraub,et al.  Presentation rate and the representation of briefly glimpsed pictures in memory. , 1980, Journal of experimental psychology. Human learning and memory.

[33]  Douglas P. Munoz,et al.  Expression of a re-centering bias in saccade regulation by superior colliculus neurons , 2001, Experimental Brain Research.

[34]  Iain D. Gilchrist,et al.  Investigating a space-variant weighted salience account of visual selection , 2007, Vision Research.

[35]  David Crundall,et al.  Effects of experience and processing demands on visual information acquisition in drivers , 1998 .

[36]  Asha Iyer,et al.  Components of bottom-up gaze allocation in natural images , 2005, Vision Research.

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

[38]  Mary M Hayhoe,et al.  Visual memory and motor planning in a natural task. , 2003, Journal of vision.

[39]  R. C. Langford How People Look at Pictures, A Study of the Psychology of Perception in Art. , 1936 .

[40]  Iain D. Gilchrist,et al.  Visual correlates of fixation selection: effects of scale and time , 2005, Vision Research.

[41]  Roland J. Baddeley,et al.  High frequency edges (but not contrast) predict where we fixate: A Bayesian system identification analysis , 2006, Vision Research.