Vision Enhancement Technique Based on Eye Tracking System

2012 ◽  
pp. 150-160 ◽  
Author(s):  
Vidas Raudonis ◽  
Agne Paulauskaite-Taraseviciene ◽  
Rytis Maskeliunas
Keyword(s):  
Eye Tracking ◽  
Tracking System ◽  
Enhancement Technique

An eye tracking system for analysis of pilots' scan paths.

1997 ◽  
Author(s):  
Paul A. Wetzel ◽  
Gretchen Krueger-Anderson ◽  
Christine Poprik ◽  
Peter Bascom
Keyword(s):  
Eye Tracking ◽  
Tracking System ◽  
Scan Paths

The Research on Eye Tracking for Gaze Tracking System

2010 ◽  
Vol 36 (8) ◽  
pp. 1051-1061 ◽  
Author(s):  
Chuang ZHANG ◽  
Jian-Nan CHI ◽  
Zhao-Hui ZHANG ◽  
Zhi-Liang WANG
Keyword(s):  
Eye Tracking ◽  
Tracking System ◽  
Gaze Tracking

scholarly journals Tracking eye-gaze in smart home systems (SHS): first insights from eye-tracking and self-report measures

2021 ◽  
Author(s):  
Federico Cassioli ◽  
Laura Angioletti ◽  
Michela Balconi
Keyword(s):  
Eye Tracking ◽  
Personality Traits ◽  
Smart Home ◽  
Near Infrared ◽  
Tracking System ◽  
Eye Gaze ◽  
Self Report ◽  
Visual Exploration ◽  
Living Room ◽  
Psychological Traits

AbstractHuman–computer interaction (HCI) is particularly interesting because full-immersive technology may be approached differently by users, depending on the complexity of the interaction, users’ personality traits, and their motivational systems inclination. Therefore, this study investigated the relationship between psychological factors and attention towards specific tech-interactions in a smart home system (SHS). The relation between personal psychological traits and eye-tracking metrics is investigated through self-report measures [locus of control (LoC), user experience (UX), behavioral inhibition system (BIS) and behavioral activation system (BAS)] and a wearable and wireless near-infrared illumination based eye-tracking system applied to an Italian sample (n = 19). Participants were asked to activate and interact with five different tech-interaction areas with different levels of complexity (entrance, kitchen, living room, bathroom, and bedroom) in a smart home system (SHS), while their eye-gaze behavior was recorded. Data showed significant differences between a simpler interaction (entrance) and a more complex one (living room), in terms of number of fixation. Moreover, slower time to first fixation in a multifaceted interaction (bathroom), compared to simpler ones (kitchen and living room) was found. Additionally, in two interaction conditions (living room and bathroom), negative correlations were found between external LoC and fixation count, and between BAS reward responsiveness scores and fixation duration. Findings led to the identification of a two-way process, where both the complexity of the tech-interaction and subjects’ personality traits are important impacting factors on the user’s visual exploration behavior. This research contributes to understand the user responsiveness adding first insights that may help to create more human-centered technology.

A Smart Eye Tracking System for Virtual Reality

2019 ◽  
Author(s):  
Bin Li ◽  
Yun Zhang ◽  
Xiujuan Zheng ◽  
Xiaoping Huang ◽  
Sheng Zhang ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Eye Tracking ◽  
Tracking System

Estimating 3-D Point-of-Regard in a Real Environment Using a Head-Mounted Eye-Tracking System

2014 ◽  
Vol 44 (4) ◽  
pp. 531-536 ◽  
Author(s):  
Kentaro Takemura ◽  
Kenji Takahashi ◽  
Jun Takamatsu ◽  
Tsukasa Ogasawara
Keyword(s):  
Eye Tracking ◽  
Tracking System ◽  
Real Environment
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