Development of Eye Fixation Points Prediction Model from Eye Tracking Data using Neural Network
نویسندگان
چکیده
منابع مشابه
Analyzing Behavioral Markers of Autistic Children Using Eye Tracking Data
Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that occurs in the early years of life and is characterized by social impairment, verbal and non-verbal communication difficulties as well as stereotypical behaviors. Rehabilitating autistic children at the early stages of growth, in which their brain is highly flexible, yields to enhanced treatment process and provid...
متن کاملDevelopment of An Artificial Neural Network Model for Asphalt Pavement Deterioration Using LTPP Data
Deterioration models are important and essential part of any Pavement Management System (PMS). These models are used to predict future pavement situation based on existence condition, parameters causing deterioration and implications of various maintenance and rehabilitation policies on pavement. The majority of these models are based on roughness which is one of the most important indices in p...
متن کاملHuman Computer Interaction Using Eye-tracking Data
The eye-tracking device records users’ eye movements in order to better understand users’ information-seeking behavior. One of our research goals was to investigate the search behavior when participants interact with a healthrelated online database. Another research goal was to explore how participants browse for health information inquiries. The result shows that the health professional partic...
متن کاملVolume Composition Using Eye Tracking Data
This paper presents a method to automate rendering parameter selection, simplifying tedious user interaction and improving the usability of visualization systems. Our approach acquires regions-of-interest for a dataset with an eye tracker and simple user interaction. Based on this importance information, we then automatically compute reasonable rendering parameters using a set of heuristic rule...
متن کاملRunning Head: Cleaning up eye tracking data using RFLs Cleaning up systematic error in eye tracking data by using required fixation locations
In the course of running an eye tracking experiment, one computer system or subsystem typically presents the stimuli to the participant and records manual responses, and another collects the eye movement data, with little interaction between the two during the course of the experiment. This article demonstrates how the two systems can interact with each other to facilitate a richer set of exper...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Technology
سال: 2017
ISSN: 2087-2100,2086-9614
DOI: 10.14716/ijtech.v8i6.717