Javascript must be enabled to continue!
Influences of Global and Local Features on Eye-Movement Patterns in Visual-Similarity Perception of Synthesized Texture Images
View through CrossRef
Global and local features are essential for visual-similarity texture perception. Therefore, understanding how people allocate their visual attention when viewing textures with global or local similarity is important. In this work, we investigate the influences of global and local features of a texture on eye-movement patterns and analyze the relationship between eye-movement patterns and visual-similarity selection. First, we synthesized textures by separately controlling global and local textural features through the primitive, grain, and point configuration (PGPC) texture model, a mathematical morphology-based texture model. Second, we conducted an experiment to acquire eye-movement data where participants identified the texture that was highly similar to the standard texture. Experiment data were obtained through an eye-tracker from 60 participants. The collected eye-tracking data were analyzed in terms of three metrics, including total fixation duration in each region of interest (ROI), fixation-point variance in each ROI, and fixation-transfer counts between different ROIs. Analysis results indicated the following. (1) The global and local features of a texture influenced eye-movement patterns. In particular, the texture image that was globally similar to the standard texture contained dispersed fixation points. By contrast, the texture image that was locally similar to the standard texture contained concentrated fixation points. The domination of global and local features influenced the viewers’ similarity choice. (2) The final visual-similarity selection was related to the fixation-transfer count between different ROIs, but not to the fixation time in each ROI. This research also extends the applicability of the mathematical morphology-based texture model to human visual perception.
Title: Influences of Global and Local Features on Eye-Movement Patterns in Visual-Similarity Perception of Synthesized Texture Images
Description:
Global and local features are essential for visual-similarity texture perception.
Therefore, understanding how people allocate their visual attention when viewing textures with global or local similarity is important.
In this work, we investigate the influences of global and local features of a texture on eye-movement patterns and analyze the relationship between eye-movement patterns and visual-similarity selection.
First, we synthesized textures by separately controlling global and local textural features through the primitive, grain, and point configuration (PGPC) texture model, a mathematical morphology-based texture model.
Second, we conducted an experiment to acquire eye-movement data where participants identified the texture that was highly similar to the standard texture.
Experiment data were obtained through an eye-tracker from 60 participants.
The collected eye-tracking data were analyzed in terms of three metrics, including total fixation duration in each region of interest (ROI), fixation-point variance in each ROI, and fixation-transfer counts between different ROIs.
Analysis results indicated the following.
(1) The global and local features of a texture influenced eye-movement patterns.
In particular, the texture image that was globally similar to the standard texture contained dispersed fixation points.
By contrast, the texture image that was locally similar to the standard texture contained concentrated fixation points.
The domination of global and local features influenced the viewers’ similarity choice.
(2) The final visual-similarity selection was related to the fixation-transfer count between different ROIs, but not to the fixation time in each ROI.
This research also extends the applicability of the mathematical morphology-based texture model to human visual perception.
Related Results
Hydatid Cyst of The Orbit: A Systematic Review with Meta-Data
Hydatid Cyst of The Orbit: A Systematic Review with Meta-Data
Abstarct
Introduction
Orbital hydatid cysts (HCs) constitute less than 1% of all cases of hydatidosis, yet their occurrence is often linked to severe visual complications. This stu...
The Power of the Wave: Activism Rainbow Region-Style
The Power of the Wave: Activism Rainbow Region-Style
Introduction The counterculture that arose during the 1960s and 1970s left lasting social and political reverberations in developed nations. This was a time of increasing affluenc...
The functions of the proprioceptors of the eye muscles
The functions of the proprioceptors of the eye muscles
This article sets out to present a fairly comprehensive review of our knowledge about the functions of the receptors that have been found in the extraocular muscles – the six muscl...
Similarity Search with Data Missing
Similarity Search with Data Missing
Similarity search is a fundamental research problem with broad applications in various research fields, including data mining, information retrieval, and machine learning. The core...
Psihološke odrednice sindroma suhog oka
Psihološke odrednice sindroma suhog oka
Introduction: Dry eye disease (DED) is a worldwide public health problem that may cause serious consequences for the patient's health. The etiology of the disease is multifactorial...
CT Metal Artifact Reduction based on Virtual Generated Artifacts Using Modified pix2pix
CT Metal Artifact Reduction based on Virtual Generated Artifacts Using Modified pix2pix
Abstract
Background: Metal artifacts introduce challenges in image-guided diagnosis or accurate dose calculations. This study aims to reduce metal artifacts from the spinal...
IMPACT OF REFRACTIVE CORRECTION ON VISUAL FATIGUE, EYE MOVEMENT AND READING SPEED IN ADULTS
IMPACT OF REFRACTIVE CORRECTION ON VISUAL FATIGUE, EYE MOVEMENT AND READING SPEED IN ADULTS
Background
Refractive errors are a leading cause of visual impairment, significantly affecting daily activities that require sustained attention, such as reading. Uncorrected refra...
A ROBUST-TEXTURE CONVOLUTIONAL NEURAL NETWORK
A ROBUST-TEXTURE CONVOLUTIONAL NEURAL NETWORK
AlexNet was a breakthrough for the convolutional neural network (CNN) and showed the greatest successful mod- ified CNN that works well with large-scale images. However, it was uns...


