The effects of task and saliency on latencies for colour and motion processing

In human visual perception, there is evidence that different visual attributes, such as colour, form and motion, have different neural-processing latencies. Specifically, recent studies have suggested that colour changes are processed faster than motion changes. We propose that the processing latencies should not be considered as fixed quantities for different attributes, but instead depend upon attribute salience and the observer's task. We asked observers to respond to high- and low-salience colour and motion changes in three different tasks. The tasks varied from having a strong motor component to having a strong perceptual component. Increasing salience led to shorter processing times in all three tasks. We also found an interaction between task and attribute: motion was processed more quickly in reaction-time tasks, whereas colour was processed more quickly in more perceptual tasks. Our results caution against making direct comparisons between latencies for processing different visual attributes without equating salience or considering task effects. More-salient attributes are processed faster than less-salient ones, and attributes that are critical for the task are also processed more quickly.     

Visual processing levels revealed by response latencies to changes in different visual attributes.

Visual latencies, and their variation with stimulus attributes, can provide information about the level in the visual system at which different attributes of the image are analysed, and decisions about them made. A change in the colour, structure or movement of a visual stimulus brings about a highly reproducible transient constriction of the pupil that probably depends on visual cortical mechanisms. We measured this transient response to changes in several attributes of visual stimuli, and also measured manual reaction times to the same stimulus changes. Through analysis of latencies, we hoped to establish whether changes in different stimulus attributes were processed by mechanisms at the same or different levels in the visual pathway. Pupil responses to a change in spatial structure or colour are almost identical, but both are ca. 40 ms slower than those to a change in light flux, which are thought to depend largely on subcortical pathways. Manual reaction times to a change in spatial structure or colour, or to the onset of coherent movement, differ reliably, and all are longer than the reaction time to a change in light flux. On average, observers take 184 ms to detect a change in light flux, 6 ms more to detect the onset of a grating, 30 ms more to detect a change in colour, and 37 ms more to detect the onset of coherent motion. The pattern of latency variation for pupil responses and reaction times suggests that the mechanisms that trigger the responses lie at different levels in cortex. Given our present knowledge of visual cortical organization, the long reaction time to the change in motion is surprising. The range of reaction times across different stimuli is consistent with decisions about the onset of a grating being made in V1 and decisions about the change in colour or change in motion being made in V4.     

The uses of colour vision: behavioural and physiological distinctiveness of colour stimuli

Colour and greyscale (black and white) pictures look different to us, but it is not clear whether the difference in appearance is a consequence of the way our visual system uses colour signals or a by-product of our experience. In principle, colour images are qualitatively different from greyscale images because they make it possible to use different processing strategies. Colour signals provide important cues for segmenting the image into areas that represent different objects and for linking together areas that represent the same object. If this property of colour signals is exploited in visual processing we would expect colour stimuli to look different, as a class, from greyscale stimuli. We would also expect that adding colour signals to greyscale signals should change the way that those signals are processed. We have investigated these questions in behavioural and in physiological experiments. We find that male marmosets (all of which are dichromats) rapidly learn to distinguish between colour and greyscale copies of the same images. The discrimination transfers to new image pairs, to new colours and to image pairs in which the colour and greyscale images are spatially different. We find that, in a proportion of neurons recorded in the marmoset visual cortex, colour-shifts in opposite directions produce similar enhancements of the response to a luminance stimulus. We conclude that colour is, both behaviourally and physiologically, a distinctive property of images.     

Detecting Unidentified Changes

Does becoming aware of a change to a purely visual stimulus necessarily cause the observer to be able to identify or localise the change or can change detection occur in the absence of identification or localisation? Several theories of visual awareness stress that we are aware of more than just the few objects to which we attend. In particular, it is clear that to some extent we are also aware of the global properties of the scene, such as the mean luminance or the distribution of spatial frequencies. It follows that we may be able to detect a change to a visual scene by detecting a change to one or more of these global properties. However, detecting a change to global property may not supply us with enough information to accurately identify or localise which object in the scene has been changed. Thus, it may be possible to reliably detect the occurrence of changes without being able to identify or localise what has changed. Previous attempts to show that this can occur with natural images have produced mixed results. Here we use a novel analysis technique to provide additional evidence that changes can be detected in natural images without also being identified or localised. It is likely that this occurs by the observers monitoring the global properties of the scene.     

A Novel GBM Saliency Detection Model Using Multi-Channel MRI

The automatic computerized detection of regions of interest (ROI) is an important step in the process of medical image processing and analysis. The reasons are many, and include an increasing amount of available medical imaging data, existence of inter-observer and inter-scanner variability, and to improve the accuracy in automatic detection in order to assist doctors in diagnosing faster and on time. A novel algorithm, based on visual saliency, is developed here for the identification of tumor regions from MR images of the brain. The GBM saliency detection model is designed by taking cue from the concept of visual saliency in natural scenes. A visually salient region is typically rare in an image, and contains highly discriminating information, with attention getting immediately focused upon it. Although color is typically considered as the most important feature in a bottom-up saliency detection model, we circumvent this issue in the inherently gray scale MR framework. We develop a novel pseudo-coloring scheme, based on the three MRI sequences, viz. FLAIR, T2 and T1C (contrast enhanced with Gadolinium). A bottom-up strategy, based on a new pseudo-color distance and spatial distance between image patches, is defined for highlighting the salient regions in the image. This multi-channel representation of the image and saliency detection model help in automatically and quickly isolating the tumor region, for subsequent delineation, as is necessary in medical diagnosis. The effectiveness of the proposed model is evaluated on MRI of 80 subjects from the BRATS database in terms of the saliency map values. Using ground truth of the tumor regions for both high- and low- grade gliomas, the results are compared with four highly referred saliency detection models from literature. In all cases the AUC scores from the ROC analysis are found to be more than 0.999 ± 0.001 over different tumor grades, sizes and positions.     

The human visual system is optimised for processing the spatial information in natural visual images

A fundamental tenet of visual science is that the detailed properties of visual systems are not capricious accidents, but are closely matched by evolution and neonatal experience to the environments and lifestyles in which those visual systems must work. This has been shown most convincingly for fish and insects. For mammalian vision, however, this tenet is based more upon theoretical arguments than upon direct observations. Here, we describe experiments that require human observers to discriminate between pictures of slightly different faces or objects. These are produced by a morphing technique that allows small, quantifiable changes to be made in the stimulus images. The independent variable is designed to give increasing deviation from natural visual scenes, and is a measure of the Fourier composition of the image (its second-order statistics). Performance in these tests was best when the pictures had natural second-order spatial statistics, and degraded when the images were made less natural. Furthermore, performance can be explained with a simple model of contrast coding, based upon the properties of simple cells in the mammalian visual cortex. The findings thus provide direct empirical support for the notion that human spatial vision is optimised to the second-order statistics of the optical environment.     

Regional Principal Color Based Saliency Detection

Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms.     

A saliency-based bottom-up visual attention model for dynamic scenes analysis

This work proposes a model of visual bottom-up attention for dynamic scene analysis. Our work adds motion saliency calculations to a neural network model with realistic temporal dynamics [(e.g., building motion salience on top of De Brecht and Saiki Neural Networks 19:1467–1474, (2006)]. The resulting network elicits strong transient responses to moving objects and reaches stability within a biologically plausible time interval. The responses are statistically different comparing between earlier and later motion neural activity; and between moving and non-moving objects. We demonstrate the network on a number of synthetic and real dynamical movie examples. We show that the model captures the motion saliency asymmetry phenomenon. In addition, the motion salience computation enables sudden-onset moving objects that are less salient in the static scene to rise above others. Finally, we include strong consideration for the neural latencies, the Lyapunov stability, and the neural properties being reproduced by the model.     

Visual Saliency Models for Text Detection in Real World

This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose. Using this scene image database and five state-of-the-art models, visual saliency maps that represent the degree of saliency of the objects are calculated. The receiver operating characteristic curve is employed in order to evaluate the saliency of scene texts, which is calculated by visual saliency models. A visualization of the distribution of scene texts and non-texts in the space constructed by three kinds of saliency maps, which are calculated using Itti''s visual saliency model with intensity, color and orientation features, is given. This visualization of distribution indicates that text characters are more salient than their non-text neighbors, and can be captured from the background. Therefore, scene texts can be extracted from the scene images. With this in mind, a new visual saliency architecture, named hierarchical visual saliency model, is proposed. Hierarchical visual saliency model is based on Itti''s model and consists of two stages. In the first stage, Itti''s model is used to calculate the saliency map, and Otsu''s global thresholding algorithm is applied to extract the salient region that we are interested in. In the second stage, Itti''s model is applied to the salient region to calculate the final saliency map. An experimental evaluation demonstrates that the proposed model outperforms Itti''s model in terms of captured scene texts.     

Where Do Neurologists Look When Viewing Brain CT Images? An Eye-Tracking Study Involving Stroke Cases

The aim of this study was to investigate where neurologists look when they view brain computed tomography (CT) images and to evaluate how they deploy their visual attention by comparing their gaze distribution with saliency maps. Brain CT images showing cerebrovascular accidents were presented to 12 neurologists and 12 control subjects. The subjects' ocular fixation positions were recorded using an eye-tracking device (Eyelink 1000). Heat maps were created based on the eye-fixation patterns of each group and compared between the two groups. The heat maps revealed that the areas on which control subjects frequently fixated often coincided with areas identified as outstanding in saliency maps, while the areas on which neurologists frequently fixated often did not. Dwell time in regions of interest (ROI) was likewise compared between the two groups, revealing that, although dwell time on large lesions was not different between the two groups, dwell time in clinically important areas with low salience was longer in neurologists than in controls. Therefore it appears that neurologists intentionally scan clinically important areas when reading brain CT images showing cerebrovascular accidents. Both neurologists and control subjects used the "bottom-up salience" form of visual attention, although the neurologists more effectively used the "top-down instruction" form.     

A texture-processing model of the ‘visual sense of number’

It has been suggested that numerosity is an elementary quality of perception, similar to colour. If so (and despite considerable investigation), its mechanism remains unknown. Here, we show that observers require on average a massive difference of approximately 40% to detect a change in the number of objects that vary irrelevantly in blur, contrast and spatial separation, and that some naive observers require even more than this. We suggest that relative numerosity is a type of texture discrimination and that a simple model computing the contrast energy at fine spatial scales in the image can perform at least as well as human observers. Like some human observers, this mechanism finds it harder to discriminate relative numerosity in two patterns with different degrees of blur, but it still outpaces the human. We propose energy discrimination as a benchmark model against which more complex models and new data can be tested.     

Airport detection in remote sensing images: a method based on saliency map

The detection of airport attracts lots of attention and becomes a hot topic recently because of its applications and importance in military and civil aviation fields. However, the complicated background around airports brings much difficulty into the detection. This paper presents a new method for airport detection in remote sensing images. Distinct from other methods which analyze images pixel by pixel, we introduce visual attention mechanism into detection of airport and improve the efficiency of detection greatly. Firstly, Hough transform is used to judge whether an airport exists in an image. Then an improved graph-based visual saliency model is applied to compute the saliency map and extract regions of interest (ROIs). The airport target is finally detected according to the scale-invariant feature transform features which are extracted from each ROI and classified by hierarchical discriminant regression tree. Experimental results show that the proposed method is faster and more accurate than existing methods, and has lower false alarm rate and better anti-noise performance simultaneously.     

Neural activities in v1 create a bottom-up saliency map

The bottom-up contribution to the allocation of exogenous attention is a saliency map, whose neural substrate is hard to identify because of possible contamination by top-down signals. We obviated this possibility using stimuli that observers could not perceive, but that nevertheless, through orientation contrast between foreground and background regions, attracted attention to improve a localized visual discrimination. When orientation contrast increased, so did the degree of attraction, and two physiological measures: the amplitude of the earliest (C1) component of the ERP, which is associated with primary visual cortex, and fMRI BOLD signals in areas V1-V4 (but not the intraparietal sulcus). Significantly, across observers, the degree of attraction correlated with the C1 amplitude and just the V1 BOLD signal. These findings strongly support the proposal that a bottom-up saliency map is created in V1, challenging the dominant view that the saliency map is generated in the parietal cortex.     

Cue combination in the motion correspondence problem

Image motion is a primary source of visual information about the world. However, before this information can be used the visual system must determine the spatio-temporal displacements of the features in the dynamic retinal image, which originate from objects moving in space. This is known as the motion correspondence problem. We investigated whether cross-cue matching constraints contribute to the solution of this problem, which would be consistent with physiological reports that many directionally selective cells in the visual cortex also respond to additional visual cues. We measured the maximum displacement limit (Dmax) for two-frame apparent motion sequences. Dmax increases as the number of elements in such sequences decreases. However, in our displays the total number of elements was kept constant while the number of a subset of elements, defined by a difference in contrast polarity, binocular disparity or colour, was varied. Dmax increased as the number of elements distinguished by a particular cue was decreased. Dmax was affected by contrast polarity for all observers, but only some observers were influenced by binocular disparity and others by colour information. These results demonstrate that the human visual system exploits local, cross-cue matching constraints in the solution of the motion correspondence problem.     

Culture Modulates Eye-Movements to Visual Novelty

Background

When viewing complex scenes, East Asians attend more to contexts whereas Westerners attend more to objects, reflecting cultural differences in holistic and analytic visual processing styles respectively. This eye-tracking study investigated more specific mechanisms and the robustness of these cultural biases in visual processing when salient changes in the objects and backgrounds occur in complex pictures.

Methodology/Principal Findings

Chinese Singaporean (East Asian) and Caucasian US (Western) participants passively viewed pictures containing selectively changing objects and background scenes that strongly captured participants'' attention in a data-driven manner. We found that although participants from both groups responded to object changes in the pictures, there was still evidence for cultural divergence in eye-movements. The number of object fixations in the US participants was more affected by object change than in the Singapore participants. Additionally, despite the picture manipulations, US participants consistently maintained longer durations for both object and background fixations, with eye-movements that generally remained within the focal objects. In contrast, Singapore participants had shorter fixation durations with eye-movements that alternated more between objects and backgrounds.

Conclusions/Significance

The results demonstrate a robust cultural bias in visual processing even when external stimuli draw attention in an opposite manner to the cultural bias. These findings also extend previous studies by revealing more specific, but consistent, effects of culture on the different aspects of visual attention as measured by fixation duration, number of fixations, and saccades between objects and backgrounds.     

Saliency changes appearance

Numerous studies have suggested that the deployment of attention is linked to saliency. In contrast, very little is known about how salient objects are perceived. To probe the perception of salient elements, observers compared two horizontally aligned stimuli in an array of eight elements. One of them was salient because of its orientation or direction of motion. We observed that the perceived luminance contrast or color saturation of the salient element increased: the salient stimulus looked even more salient. We explored the possibility that changes in appearance were caused by attention. We chose an event-related potential indexing attentional selection, the N2pc, to answer this question. The absence of an N2pc to the salient object provides preliminary evidence against involuntary attentional capture by the salient element. We suggest that signals from a master saliency map flow back into individual feature maps. These signals boost the perceived feature contrast of salient objects, even on perceptual dimensions different from the one that initially defined saliency.     

An implicit measure of undetected change

Several paradigms (e.g. change blindness, inattentional blindness, transsaccadic integration) indicate that observers are often very poor at reporting changes to their visual environment. Such evidence has been used to suggest that the spatio-temporal coherence needed to represent change can only occur in the presence of focused attention. However, those studies almost always rely on explicit reports. It remains a possibility that the visual system can implicitly detect change, but that in the absence of focused attention, the change does not reach awareness and consequently is not reported. To test this possibility, we used a simple change detection paradigm coupled with a speeded orientation discrimination task. Even when observers reported being unaware of a change in an item's orientation, its final orientation effectively biased their response in the orientation discrimination task. Both in aware and unaware trials, errors were most frequent when the changed item and the probe had incongruent orientations. These results demonstrate that the nature of the change can be represented in the absence of awareness.     

Associatieve visuele agnosie. De minder zichtbare gevolgen van een herseninfarct

After a cerebral infarction, some patients acutely demonstrate contralateral hemiplegia, or aphasia. Those are the obvious symptoms of a cerebral infarction. However, less visible but burdensome consequences may go unnoticed without closer investigation. The importance of a thorough clinical examination is exemplified by a single case study of a 72-year-old, right-handed male. Two years before he had suffered from an ischemic stroke in the territory of the left posterior cerebral artery, with right homonymous hemianopia and global alexia (i.e., impairment in letter recognition and profound impairment of reading) without agraphia. Naming was impaired on visual presentation (20%-39% correct), but improved significantly after tactile presentation (87% correct) or verbal definition (89%). Pre-semantic visual processing was normal (correct matching of different views of the same object), as was his access to structural knowledge from vision (he reliably distinguished real objects from non-objects). On a colour decision task he reliably indicated which of two items was coloured correctly. Though he was unable to mime how visually presented objects were used, he more reliably matched pictures of objects with pictures of a mime artist gesturing the use of the object. He obtained normal scores on word definition (WAIS-III), synonym judgment and word-picture matching tasks with perceptual and semantic distractors. He however failed when he had to match physically dissimilar specimens of the same object or when he had to decide which two of five objects were related associatively (Pyramids and Palm Trees Test). The patient thus showed a striking contrast in his intact ability to access knowledge of object shape or colour from vision and impaired functional and associative knowledge. As a result, he could not access a complete semantic representation, required for activating phonological representations to name visually presented objects. The pattern of impairments and preserved abilities is considered to be a specific difficulty to access a full semantic representation from an intact structural representation of visually presented objects, i.e., a form of visual object agnosia.     

Summation of perceptual cues in natural visual scenes

Natural visual scenes are rich in information, and any neural system analysing them must piece together the many messages from large arrays of diverse feature detectors. It is known how threshold detection of compound visual stimuli (sinusoidal gratings) is determined by their components' thresholds. We investigate whether similar combination rules apply to the perception of the complex and suprathreshold visual elements in naturalistic visual images. Observers gave magnitude estimations (ratings) of the perceived differences between pairs of images made from photographs of natural scenes. Images in some pairs differed along one stimulus dimension such as object colour, location, size or blur. But, for other image pairs, there were composite differences along two dimensions (e.g. both colour and object-location might change). We examined whether the ratings for such composite pairs could be predicted from the two ratings for the respective pairs in which only one stimulus dimension had changed. We found a pooling relationship similar to that proposed for simple stimuli: Minkowski summation with exponent 2.84 yielded the best predictive power (r=0.96), an exponent similar to that generally reported for compound grating detection. This suggests that theories based on detecting simple stimuli can encompass visual processing of complex, suprathreshold stimuli.     

Defining Natural Categories in Acoustic Signals: Comparison of Three Methods Applied to ‘Chick-a-dee’ Call Notes

Chicks were trained to discriminate between two identical boxes on the basis of their position. Subsequently, the colour of parts of the positive (reinforced) box was changed and chicks were retrained. Results showed that chicks were more or less impaired during retraining depending on the spatial distribution of the changed stimuli. Chicks behaved as if a figure (a disc or a spot of dots) painted on a box was irrelevant to them, whereas they did respond to changes in the colour of a uniformly coloured box or of scattered dots painted on a box. Similar results were obtained in simultaneous discrimination learning tasks involving addition of cues (e.g. colour plus position). Addition of cues facilitated learning using boxes the same colour all over or with painted scattered dots, but not using boxes with a disc or a spot of dots. Furthermore, addition of shape and position information had different outcomes depending on the use of three-dimensional objects or of painted figures: learning facilitation occurred only using three-dimensional objects. Results are interpreted in terms of an “object hypothesis”, and the validity and usefulness of traditional terms such as cues is questioned.