Five important trends have emerged from recent work on computational models of focal visual attention that emphasize the bottom-up, image-based control of attentional deployment. First, the perceptual saliency of stimuli critically depends on the surrounding context. Second, a unique 'saliency map' that topographically encodes for stimulus conspicuity over the visual scene has proved to be an efficient and plausible bottom-up control strategy. Third, inhibition of return, the process by which the currently attended location is prevented from being attended again, is a crucial element of attentional deployment. Fourth, attention and eye movements tightly interplay, posing computational challenges with respect to the coordinate system used to control attention. And last, scene understanding and object recognition strongly constrain the selection of attended locations. Insights from these five key areas provide a framework for a computational and neurobiological understanding of visual attention.

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Computational modelling of visual attention.

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The outside world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the governing laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Several lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual \"filling in,\" visual stability despite eye movements, change blindness, sensory substitution, and color perception.

A sensorimotor account of vision and visual consciousness-Authors' Response-Acting out our sensory experience

A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

When natural scenes are viewed, a multitude of objects that are stable in their environments are brought in and out of view by eye movements. The posterior parietal cortex is crucial for the analysis of space, visual attention and movement 1 . Neurons in one of its subdivisions, the lateral intraparietal area (LIP), have visual responses to stimuli appearing abruptly at particular retinal locations (their receptive fields)2. We have tested the responses of LIP neurons to stimuli that entered their receptive field by saccades. Neurons had little or no response to stimuli brought into their receptive field by saccades, unless the stimuli were behaviourally significant. We established behavioural significance in two ways: either by making a stable stimulus task-relevant, or by taking advantage of the attentional attraction of an abruptly appearing stimulus. Our results show that under ordinary circumstances the entire visual world is only weakly represented in LIP. The visual representation in LIP is sparse, with only the most salient or behaviourally relevant objects being strongly represented.

The representation of visual salience in monkey parietal cortex

The measurement of pupil diameter in psychology (in short, "pupillometry") has just celebrated 50 years. The method established itself after the appearance of three seminal studies (Hess & Polt, 1960, 1964; Kahneman & Beatty, 1966). Since then, the method has continued to play a significant role within the field, and pupillary responses have been successfully used to provide an estimate of the "intensity" of mental activity and of changes in mental states, particularly changes in the allocation of attention and the consolidation of perception. Remarkably, pupillary responses provide a continuous measure regardless of whether the participant is aware of such changes. More recently, research in neuroscience has revealed a tight correlation between the activity of the locus coeruleus (i.e., the "hub" of the noradrenergic system) and pupillary dilation. As we discuss in this short review, these neurophysiological findings provide new important insights to the meaning of pupillary responses for mental activity. Finally, given that pupillary responses can be easily measured in a noninvasive manner, occur from birth, and can occur in the absence of voluntary, conscious processes, they constitute a very promising tool for the study of preverbal (e.g., infants) or nonverbal participants (e.g., animals, neurological patients).

Pupillometry: A Window to the Preconscious?

It has long been documented that emotional and sensory events elicit a pupillary dilation. Is the pupil response a reliable marker of a visual detection event while viewing complex imagery? In two experiments where viewers were asked to report the presence of a visual target during rapid serial visual presentation (RSVP), pupil dilation was significantly associated with target detection. The amplitude of the dilation depended on the frequency of targets and the time of target presentation relative to the start of the trial. Larger dilations were associated with trials having fewer targets and with targets viewed earlier in the run. We found that dilation was influenced by, but not dependent on, the requirement of a button press. Interestingly, we also found that dilation occurred when viewers fixated a target but did not report seeing it. We will briefly discuss the role of noradrenaline in mediating these pupil behaviors.

Pupil dilation during visual target detection.

A pupilometer having a pupil irregularity or non-uniformity detection capability. The pupilometer may comprise an imaging sensor for generating signals representative of a pupil of an eye, a data processor; and a program executable by the data processor for enabling the data processor to process signals received from the imaging sensor and to thereby identify one or more regions of non-uniformity within an image of a perimeter of the pupil. The pupilometer may incorporate several innovative calibration and thresholding routines and may provide the basis for an innovative medical diagnostics system, when coupled to a network containing a suitable medical database and data processing hardware.

Pupilometer with pupil irregularity detection capability

Pupilometer with pupil irregularity detection, pupil tracking, and pupil response detection capability, glaucoma screening capability, intracranial pressure detection capability, and ocular aberration measurement capability

Studying neural activity during natural viewing conditions is not often attempted. Isolating the neural response of a single saccade is necessary to study neural activity during natural viewing; however, the close temporal spacing of saccades that occurs during natural viewing makes it difficult to determine the response to a single saccade. Herein, a general linear model (GLM) approach is applied to estimate the EEG neural saccadic response for different segments of the saccadic main sequence separately. It is determined that, in visual search conditions, neural responses estimated by conventional event-related averaging are significantly and systematically distorted relative to GLM estimates due to the close temporal spacing of saccades during visual search. Before the GLM is applied, analyses are applied that demonstrate that saccades during visual search with intersaccadic spacings as low as 100–150 ms do not exhibit significant refractory effects. Therefore, saccades displaying different intersaccadic spacings during visual search can be modeled using the same regressor in a GLM. With the use of the GLM approach, neural responses were separately estimated for five different ranges of saccade amplitudes during visual search. Occipital responses time locked to the onsets of saccades during visual search were found to account for, on average, 79 percent of the variance of EEG activity in a window 90–200 ms after the onsets of saccades for all five saccade amplitude ranges that spanned a range of 0.2–6.0 degrees. A GLM approach was also used to examine the lateralized ocular artifacts associated with saccades. Possible extensions of the methods presented here to account for the superposition of microsaccades in event-related EEG studies conducted in nominal fixation conditions are discussed.

Neural saccadic response estimation during natural viewing

Systems and methods for performing intelligent image processing Image processing systems and methods in accordance with the present invention may select algorithms for processing collections of images by comparing algorithmic region of interest (aROI) data to stored human visual region of interest (hROI) data to select from a database of available transformation algorithms an optimal algorithm or group of algorithms to be used in transforming data comprising the collection or collections of images The selected algorithm(s) may then be used, for example, in data compression, image enhancement or database query functions

Claudio M. Privitera

Papers

Pupil dilation during visual target detection.

Pupilometer with pupil irregularity detection capability

Pupilometer with pupil irregularity detection, pupil tracking, and pupil response detection capability, glaucoma screening capability, intracranial pressure detection capability, and ocular aberration measurement capability

Neural saccadic response estimation during natural viewing

Intelligent systems and methods for processing image data based upon anticipated regions of visual interest