IMITATING HUMAN VISUAL ATTENTION AND REPRODUCING OPTICAL ILLUSIONS BY ANT SCAN

2003 ◽  
Vol 03 (02) ◽  
pp. 157-166 ◽  
Author(s):  
UGO VALLONE ◽  
ALAIN MÉRIGOT
Keyword(s):  
Visual Attention ◽  
Human Beings ◽  
Optical Illusion ◽  
Qualitative Explanation ◽  
New Agents ◽  
Optical Illusions ◽  
Emergent Phenomenon ◽  
New Strategy ◽  
Static Images ◽  
Human Visual Attention

This article describes a new strategy for analyzing contours in static images. The goal of this analysis is to find the interest centres in the images and then to explain some common optical illusion phenomena. The approach proposed is based on a modified version of the Ant Colony Optimization paradigm named Ant Scan (here introduced). Ant Scan is different from the ACO meta-heuristic principally in the mechanism of exploration of the interest space (the image to be analyzed). Experimental results have shown that interactions among these new agents (based on communication by pheromone) can generate another type of emergent phenomenon that can be utilized to explain how human beings process static images. Classical optical illusions have been analyzed with this new model and a qualitative explanation of how they act is provided.

Information Processing in Visual System - Optical Illusion and Visual Mechanism

2001 ◽  
Vol 13 (6) ◽  
pp. 569-574
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Information Processing ◽  
Visual System ◽  
Visual Function ◽  
External World ◽  
Automated System ◽  
Human Beings ◽  
Optical Illusion ◽  
Optical Illusions ◽  
Visual Mechanism ◽  
Human Visual Mechanism

Human beings obtain big amount of information from the external world through their visual system. Automated system such as robot must provide the visual functions for their flexible operations in 3-D circumstances. In order to realize the visual function artificially, we would be better to learn from the human visual mechanism. Optical illusions would be a pure reflection of the human visual mechanism; they can be used for investigating human visual mechanism. New types of optical illusion with binocular viewing are introduced and investigated.

scholarly journals Saliency-Based Gaze Visualization for Eye Movement Analysis

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5178
Author(s):  
Sangbong Yoo ◽  
Seongmin Jeong ◽  
Seokyeon Kim ◽  
Yun Jang
Keyword(s):  
Eye Movements ◽  
Visual Attention ◽  
Eye Movement ◽  
Visual Stimuli ◽  
Saliency Map ◽  
Gaze Behavior ◽  
The Gaze ◽  
Movement Data ◽  
Visual Clues ◽  
Human Visual Attention

Gaze movement and visual stimuli have been utilized to analyze human visual attention intuitively. Gaze behavior studies mainly show statistical analyses of eye movements and human visual attention. During these analyses, eye movement data and the saliency map are presented to the analysts as separate views or merged views. However, the analysts become frustrated when they need to memorize all of the separate views or when the eye movements obscure the saliency map in the merged views. Therefore, it is not easy to analyze how visual stimuli affect gaze movements since existing techniques focus excessively on the eye movement data. In this paper, we propose a novel visualization technique for analyzing gaze behavior using saliency features as visual clues to express the visual attention of an observer. The visual clues that represent visual attention are analyzed to reveal which saliency features are prominent for the visual stimulus analysis. We visualize the gaze data with the saliency features to interpret the visual attention. We analyze the gaze behavior with the proposed visualization to evaluate that our approach to embedding saliency features within the visualization supports us to understand the visual attention of an observer.

scholarly journals Rethinking human visual attention: Spatial cueing effects and optimality of decisions by honeybees, monkeys and humans

2013 ◽  
Vol 85 ◽  
pp. 5-19 ◽  
Author(s):  
Miguel P. Eckstein ◽  
Stephen C. Mack ◽  
Dorion B. Liston ◽  
Lisa Bogush ◽  
Randolf Menzel ◽  
...  
Keyword(s):  
Visual Attention ◽  
Spatial Cueing ◽  
Human Visual Attention

scholarly journals Bottom-up visual attention model for still image: a preliminary study

2020 ◽  
Vol 6 (1) ◽  
pp. 82
Author(s):  
Adhi Prahara ◽  
Murinto Murinto ◽  
Dewi Pramudi Ismi
Keyword(s):  
Visual Attention ◽  
Object Detection ◽  
Video Compression ◽  
Saliency Map ◽  
Bottom Up ◽  
Attention Model ◽  
Intrinsic Cues ◽  
Preliminary Study ◽  
Segmentation Image ◽  
Human Visual Attention

The philosophy of human visual attention is scientifically explained in the field of cognitive psychology and neuroscience then computationally modeled in the field of computer science and engineering. Visual attention models have been applied in computer vision systems such as object detection, object recognition, image segmentation, image and video compression, action recognition, visual tracking, and so on. This work studies bottom-up visual attention, namely human fixation prediction and salient object detection models. The preliminary study briefly covers from the biological perspective of visual attention, including visual pathway, the theory of visual attention, to the computational model of bottom-up visual attention that generates saliency map. The study compares some models at each stage and observes whether the stage is inspired by biological architecture, concept, or behavior of human visual attention. From the study, the use of low-level features, center-surround mechanism, sparse representation, and higher-level guidance with intrinsic cues dominate the bottom-up visual attention approaches. The study also highlights the correlation between bottom-up visual attention and curiosity.

The rhythm of the eyes: Overt and covert attentional pointing

1997 ◽  
Vol 20 (4) ◽  
pp. 747-747 ◽  
Author(s):  
John M. Findlay ◽  
Valerie Brown ◽  
Iain D. Gilchrist
Keyword(s):  
Visual Attention ◽  
Division Of Labour ◽  
Human Vision ◽  
Detailed Account ◽  
Attentional Processes ◽  
Target Article ◽  
Human Visual Attention

This commentary centres around the system of human visual attention. Although generally supportive of the position advocated in the target article, we suggest that the detailed account overestimates the capacities of active human vision. Limitations of peripheral search and saccadic accuracy are discussed in relation to the division of labour between covert and overt attentional processes.

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