Modeling visual attention on scenes

International audienceLa modélisation computationelle de l'attention visuelle connaît actuellement un essor considérable. Les premières modèles, purement basés sur l'attention dite exogène, permettent de calculer une carte de saillance indiquant les zones d'intérêt visuel d'une image. Cependant, afin d'améliorer cette prédiction, il s'avère nécessaire de prendre en compte des informations de plus haut niveaux relatives à l'attention endogène, c'est à dire des informations liées aux processus cognitifs. Afin de rendre compte de cette problématique, le présent article décrit un certain nombre de modèles exogènes ainsi que des modèles intégrant de la connaissance a priori. Les méthodes d'évaluation des performances sont également décrites. Afin d'aller plus loin dans la modélisation et dans la compréhension des processus cognitifs, de nouvelles perspectives et direction d'études sont exposées

Web users with autism: eye tracking evidence for differences

Anecdotal evidence suggests that people with autism may have different processing strategies when accessing the web. However, limited empirical evidence is available to support this. This paper presents an eye tracking study with 18 participants with high-functioning autism and 18 neurotypical participants to investigate the similarities and differences between these two groups in terms of how they search for information within web pages. According to our analysis, people with autism are likely to be less successful in completing their searching tasks. They also have a tendency to look at more elements on web pages and make more transitions between the elements in comparison to neurotypical people. In addition, they tend to make shorter but more frequent fixations on elements which are not directly related to a given search task. Therefore, this paper presents the first empirical study to investigate how people with autism differ from neurotypical people when they search for information within web pages based on an in-depth statistical analysis of their gaze patterns

General anaesthetic and airway management practice for obstetric surgery in England: a prospective, multi-centre observational study

There are no current descriptions of general anaesthesia characteristics for obstetric surgery, despite recent changes to patient baseline characteristics and airway management guidelines. This analysis of data from the direct reporting of awareness in maternity patients' (DREAMY) study of accidental awareness during obstetric anaesthesia aimed to describe practice for obstetric general anaesthesia in England and compare with earlier surveys and best-practice recommendations. Consenting patients who received general anaesthesia for obstetric surgery in 72 hospitals from May 2017 to August 2018 were included. Baseline characteristics, airway management, anaesthetic techniques and major complications were collected. Descriptive analysis, binary logistic regression modelling and comparisons with earlier data were conducted. Data were collected from 3117 procedures, including 2554 (81.9%) caesarean deliveries. Thiopental was the induction drug in 1649 (52.9%) patients, compared with propofol in 1419 (45.5%). Suxamethonium was the neuromuscular blocking drug for tracheal intubation in 2631 (86.1%), compared with rocuronium in 367 (11.8%). Difficult tracheal intubation was reported in 1 in 19 (95%CI 1 in 16-22) and failed intubation in 1 in 312 (95%CI 1 in 169-667). Obese patients were over-represented compared with national baselines and associated with difficult, but not failed intubation. There was more evidence of change in practice for induction drugs (increased use of propofol) than neuromuscular blocking drugs (suxamethonium remains the most popular). There was evidence of improvement in practice, with increased monitoring and reversal of neuromuscular blockade (although this remains suboptimal). Despite a high risk of difficult intubation in this population, videolaryngoscopy was rarely used (1.9%)

New Insights into Ambient and Focal Visual Fixations using an Automatic Classification Algorithm

Overt visual attention is the act of directing the eyes toward a given area. These eye movements are characterised by saccades and fixations. A debate currently surrounds the role of visual fixations. Do they all have the same role in the free viewing of natural scenes? Recent studies suggest that at least two types of visual fixations exist: focal and ambient. The former is believed to be used to inspect local areas accurately, whereas the latter is used to obtain the context of the scene. We investigated the use of an automated system to cluster visual fixations in two groups using four types of natural scene images. We found new evidence to support a focal-ambient dichotomy. Our data indicate that the determining factor is the saccade amplitude. The dependence on the low-level visual features and the time course of these two kinds of visual fixations were examined. Our results demonstrate that there is an interplay between both fixation populations and that focal fixations are more dependent on low-level visual features than are ambient fixations

New insights on ambient and focal visual fixations using an automatic classification algorithm

International audienceOvert visual attention is the act of directing eyes towards a given area. These eye movements are characterized by saccades and fixations. A debate currently concerns the role of visual fixations. Do they all have the same role in free viewing of natural scenes? Recent studies suggest that there exist at least two kinds of visual fixations called focal and ambient ones. The former would be used to inspect accurately local areas whereas the latter would be used to grab the context of the scene. We investigate in this paper an automatic solution to cluster visual fixations in two groups using four types of natural scene images. We give new evidences supporting a focal-ambient dichotomy. Our clustering reveals that the determining factor is the amplitude of saccade. The dependence on the low-level visual features and the time course of these two kinds of visual fixations are examined. Results demonstrate that there is an interplay between both fixation populations and that focal fixations would be much more dependent on low-level visual features and centred than ambient ones

Medium Spatial Frequencies, a Strong Predictor of Salience

International audienceThe extent to which so-called low-level features are relevant to predict gaze allocation has been widely studied recently. However, the conclusions are contradictory. Edges and luminance contrasts seem to be always involved, but literature is conflicting about contribution of the different spatial scales. It appears that experiments using an-made scenes lead to the conclusion that fixation location can be efficiently discriminated using high-frequency information, whereas mid- or low frequencies are more discriminative for natural scenes. This paper focuses on the importance of spatial scale to predict visual attention. We propose a fast attentional model and study which frequency band predicts the best fixation locations during free-viewing task. An eye-tracking experiment has been conducted using different scene categories defined by their Fourier spectrums (Coast, Open-Country, Mountain, and Street). We found that medium frequencies (0.7-1.3 cycles per degree) globally allowed the best prediction of attention, with variability among categories. Fixation locations were found to be more predictable using medium to high frequencies in man-made street scenes and low to medium frequencies in natural landscape scenes

A Visuospatial Planning Task Coupled with Eye-Tracker and Electroencephalogram Systems

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