Image complexity measure based on visual attention

Silva, Matthieur Perreira Da; Courboulay, Vincent; Estraillier, Pascal

doi:10.1109/icip.2011.6116371

Cited by 25 publications

(13 citation statements)

References 12 publications

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“…To adjust low level image features, we used the SHINE-Toolbox for MATLAB (Willenbockel et al, 2010). Image complexity was measured by employing a method based on the compression rate of previously generated saliency maps (Da Silva, Courboulay, & Estraillier, 2011). We generated "Itti-Koch-Niebur saliency maps" for each image (Itti, Koch, & Niebur, 1998) by using the graph-based visual saliency (GBVS) algorithm (Harel, Koch, & Perona, 2007).…”

Section: Apparatus and Materialsmentioning

confidence: 99%

Startle effects on saccadic responses to emotional target stimuli

et al. 2013

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Startle stimuli elicit various physiological and cognitive responses. This study investigated whether acoustic startle stimuli affect saccadic reactions in an emotional pro- or antisaccade task. Startle probes were presented either 500 ms before or simultaneous with an imperative stimulus that indicated whether a saccade towards or away from positive, neutral, or negative peripheral target pictures had to be performed. Valence interacted with saccade direction according to an approach-avoidance pattern of gaze behavior, with delayed prosaccades to negative targets and antisaccades away from positive targets. Acoustic startle stimuli preceding the presentation of peripheral target pictures speeded up the initiation saccades, irrespective of stimulus valence. Results indicate a speeding of cognitive-motor processing by preceding startle stimuli.

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Section: Apparatus and Materialsmentioning

confidence: 99%

Startle effects on saccadic responses to emotional target stimuli

et al. 2013

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“…On the other hand, inFigures 2-3, the fixations were clustered in the embedded shape indicating the correct response(Nisiforou & Laghos, 2012). Since the perception of complexity is correlated with the variety in the visual stimulus, visual model may also look complicated if its parts are difficult to identify and separate from each other (DaSilva, Courboulay, & Estraillier, 2011).…”

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confidence: 99%

Do the eyes have it? Using eye tracking to assess students cognitive dimensions

Nisiforou

Laghos

2013

Educational Media International

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Field dependence/independence (FD/FI) is a significant dimension of cognitive styles. The paper presents results of a study that seeks to identify individuals' level of field independence during visual stimulus tasks processing. Specifically, it examined the relationship between the Hidden Figure Test (HFT) scores and the eye tracking metrics. Moreover, it explored whether differences exist among the cognitive groups, in terms of the time taken to complete the given tasks. A sample of 16 PhD students recruited from a Public University in Cyprus was classified into Field-Dependent, Field-Independent and Field-Neutral learners. Data were collected and analysed through the use of eye tracking and SPSS statistics. Results revealed a statistical significant correlation between the scores retrieved from the HFT and the Eye tracker. Additionally, the FD and the FI groups differ with respect to the tasks time completion. The findings revealed the potential of eye tracking to be used as a tool in assessing users' cognitive traits. Finally, the vision of further agenda and some practical implications for instructional designers and educators are addressed.

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“…According to Dillon and Watson (1996) recommendations, psychological measures of individual differences are in need to raise potentials for the generalization of HCI outcomes. Since the perception of complexity is correlated with the variety in the visual stimulus a visual pattern may also look complex if its parts are difficult to identify and separate from each other (DaSilva et al, 2011). Therefore, cognitive psychological theories and methods should be further applied to human-computer interaction to interpret users' individual needs and cognitive traits.…”

Section: User Cognitive Characteristics Visual Complexity and Human-mentioning

confidence: 99%

Field Dependence–Independence and Eye Movement Patterns: Investigating Users’ Differences Through an Eye Tracking Study

Nisiforou

Laghos

2015

Interact. Comput.

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The notion that users' characteristics such as the cognitive ability affect their visual information processing is continuously increasing. This eye tracking user study investigated the association between adults' (N = 54) cognitive style and eye movement (EM) patterns while interacting with a set of visual tasks. Users' cognitive type was measured with the use of the Hidden Figures Test (HFT), which classifies them into field dependent (FD), field neutral (FN) and field independent (FI) individuals. Overall, the psychometric measures and the eye tracking-derived data were statistically examined revealing significant differences and large effect sizes among the two variables tested. Particularly, the findings demonstrated that the field dependence group exemplifies a more disoriented and disorganized EM activity. Hence, greater numbers of fixations and saccades are generated, contrary to the FN or FI users'. This research study adds further to the evidence and theory base of human-computer interaction for applications in the user-centred design by identifying how users' differences in cognitive style can be manifested in eye gaze patterns. RESEARCH HIGHLIGHTS • Field dependence-independence (FD-I) cognitive style affects eye movement (EM) behaviour. • EM behaviour differs significantly between different cognitive groups. • Field dependence (FD) group produces a disoriented EM activity. • FD group generates the greatest numbers of fixations and saccades. • FD-I style can be used as a prospective component of user-centred design.

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Image complexity measure based on visual attention

Cited by 25 publications

References 12 publications

Startle effects on saccadic responses to emotional target stimuli

Startle effects on saccadic responses to emotional target stimuli

Do the eyes have it? Using eye tracking to assess students cognitive dimensions

Field Dependence–Independence and Eye Movement Patterns: Investigating Users’ Differences Through an Eye Tracking Study

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