Exploring eye movement analysis as a measure of selective visual attention in brain injured individuals

Primary Objective: To investigate the utility of using a new method of assessment for deficits in selective visual attention (SVA). Methods and Procedures: An independent groups design compared six participants with brain injuries with six participants from a non-brain injured control group. The Sensomotoric Instruments Eye Movement system with remote eye-tracking device (eye camera), and 2 sets of eight stimuli were employed to determine if the camera would be a sensitive discriminator of SVA in these groups. Main Outcomes and Results: The attention profile displayed by the brain injured group showed that they were slower, made more errors, were less accurate, and more indecisive than the control group. Conclusions: The utility of eye movement analysis as an assessment method was established, with implications for rehabilitation requiring further development. Key words: selective visual attention, eye movement analysis, brain injury

Visual attention to food cues in obesity: An eye‐tracking study.

Objective
Based on the theory of incentive sensitization, the aim of this study was to investigate differences in attentional processing of food-related visual cues between normal-weight and overweight/obese males and females.

Methods
Twenty-six normal-weight (14M, 12F) and 26 overweight/obese (14M, 12F) adults completed a visual probe task and an eye-tracking paradigm. Reaction times and eye movements to food and control images were collected during both a fasted and fed condition in a counterbalanced design.

Results
Participants had greater visual attention towards high-energy-density food images compared to low-energy-density food images regardless of hunger condition. This was most pronounced in overweight/obese males who had significantly greater maintained attention towards high-energy-density food images when compared with their normal-weight counterparts however no between weight group differences were observed for female participants.

Conclusions
High-energy-density food images appear to capture visual attention more readily than low-energy-density food images. Results also suggest the possibility of an altered visual food cue-associated reward system in overweight/obese males. Attentional processing of food cues may play a role in eating behaviors thus should be taken into consideration as part of an integrated approach to curbing obesity.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Attentional bias to food-related visual cues: is there a role in obesity?

The incentive sensitisation model of obesity suggests that modification of the dopaminergic associated reward systems in the brain may result in increased awareness of food-related visual cues present in the current food environment. Having a heightened awareness of these visual food cues may impact on food choices and eating behaviours with those being most aware of or demonstrating greater attention to food-related stimuli potentially being at greater risk of overeating and subsequent weight gain. To date, research related to attentional responses to visual food cues has been both limited and conflicting. Such inconsistent findings may in part be explained by the use of different methodological approaches to measure attentional bias and the impact of other factors such as hunger levels, energy density of visual food cues and individual eating style traits that may influence visual attention to food-related cues outside of weight status alone. This review examines the various methodologies employed to measure attentional bias with a particular focus on the role that attentional processing of food-related visual cues may have in obesity. Based on the findings of this review, it appears that it may be too early to clarify the role visual attention to food-related cues may have in obesity. Results however highlight the importance of considering the most appropriate methodology to use when measuring attentional bias and the characteristics of the study populations targeted while interpreting results to date and in designing future studies.

Deep Head Pose: Gaze-Direction Estimation in Multimodal Video

In this paper we present a convolutional neuralnetwork (CNN)-based model for human head pose estimation inlow-resolution multi-modal RGB-D data. We pose the problemas one of classification of human gazing direction. We furtherfine-tune a regressor based on the learned deep classifier. Next wecombine the two models (classification and regression) to estimateapproximate regression confidence. We present state-of-the-artresults in datasets that span the range of high-resolution humanrobot interaction (close up faces plus depth information) data tochallenging low resolution outdoor surveillance data. We buildupon our robust head-pose estimation and further introduce anew visual attention model to recover interaction with theenvironment. Using this probabilistic model, we show thatmany higher level scene understanding like human-human/sceneinteraction detection can be achieved. Our solution runs inreal-time on commercial hardware

Dopaminergic genotype biases spatial attention in healthy children

In everyday life, our sensory system is bombarded with visual input and we rely upon attention to select only those inputs that are relevant to behavioural goals. Typically, humans can shift their attention from one visual field to the other with little cost to perception. In cases of, unilateral neglect', however, there is a persistent bias of spatial attention towards the same side as the damaged cerebral hemisphere. We used a visual orienting task to examine the influence of functional polymorphisms of the dopamine transporter gene (DAT1) on individual differences in spatial attention in normally developing children. DAT1 genotype significantly influenced spatial bias. Healthy children who were homozygous for alleles that influence the expression of dopamine transporters in the brain displayed inattention for left-sided stimuli, whereas heterozygotes did not. Our data provide the first evidence in healthy individuals of a genetically mediated bias in spatial attention that is related to dopamine signalling.

The control of social attention from 1 to 4 months

The control of social attention during early infancy was investigated in two studies. In both studies, an adult turned towards one of two targets within the infant's immediate visual field. We tested: (a) whether infants were able to follow the direction of the adult's head turn; and (b) whether following a head turn was accompanied by further gaze shifts between experimenter and target. In the first study, 1-month-olds did not demonstrate attention following at the group level. In addition, those infants who turned towards the same target remained fixed on it and did not shift attention again. In Study 2, we tested infants longitudinally at 2-4 months. At the group level, infants followed the adult's head turn at 3 and 4 months but not at 2 months. Those infants who turned towards the same target at 3 and 4 months also shifted gaze back and forth between experimenter and target. By 3 months, infants seem able to capitalize on the social environment to disengage and distribute attention more flexibly. The results support the claim that the control of social attention begins in early infancy, and are consistent with the hypothesis that following the attention of other people is dependent on the development of disengagement skills.

Visual function and dysfunction in early and late age-related maculopathy

Late age-related maculopathy (ARM) is responsible for the majority of blind registrations in the Western world among persons over 50 years of age. It has devastating effects on quality of life and independence and is becoming a major public health concern. Current treatment options are limited and most aim to slow progression rather than restore vision; therefore, early detection to identify those patients most suitable for these interventions is essential. In this work, we review the literature encompassing the investigation of visual function in ARM in order to highlight those visual function parameters which are affected very early in the disease process. We pay particular attention to measures of acuity, contrast sensitivity (CS), cone function, electrophysiology, visual adaptation, central visual field sensitivity and metamorphopsia. We also consider the impact of bilateral late ARM on visual function as well as the relationship between measures of vision function and self-reported visual functioning. Much interest has centred on the identification of functional changes which may predict progression to neovascular disease; therefore, we outline the longitudinal studies, which to date have reported dark-adaptation time, short-wavelength cone sensitivity, colour-match area effect, dark-adapted foveal sensitivity, foveal flicker sensitivity, slow recovery from glare and slower foveal electroretinogram implicit time as functional risk factors for the development of neovascular disease. Despite progress in this area, we emphasise the need for longitudinal studies designed in light of developments in disease classification and retinal imaging, which would ensure the correct classification of cases and controls, and provide increased understanding of the natural course and progression of the disease and further elucidate the structure-function relationships in this devastating disorder.

A biologically inspired appearance model for robust visual tracking

In this work, we propose a biologically inspired appearance model for robust visual tracking. Motivated in part by the success of the hierarchical organization of the primary visual cortex (area V1), we establish an architecture consisting of five layers: whitening, rectification, normalization, coding and polling. The first three layers stem from the models developed for object recognition. In this paper, our attention focuses on the coding and pooling layers. In particular, we use a discriminative sparse coding method in the coding layer along with spatial pyramid representation in the pooling layer, which makes it easier to distinguish the target to be tracked from its background in the presence of appearance variations. An extensive experimental study shows that the proposed method has higher tracking accuracy than several state-of-the-art trackers.