Automating the process of gaze tracking data using soft clustering

Jeevithashree, DV and Ray, Pallavi and Natarajan, P and Pradipta, Biswas (2018) Automating the process of gaze tracking data using soft clustering. In: 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017, 6-7 July 2017, Kannur, pp. 449-456.

PDF ICICICT_2018_449-456_2018 .pdf - Published Version Restricted to Registered users only Download (573kB) | Request a copy

Abstract

The aim of the paper is to automate the processing of gaze tracking data through soft clustering techniques. Standard analysis software for eye gaze tracking data requires users to define areas of interest, which may not be best option for exploratory analysis, where users may want to analyze eye gaze tracking data to know the area of interest. We have presented results on using Fuzzy c-means and Expectation Maximization algorithms on gaze tracking data and using an entropy based cluster validation index, we tried to automate identification of areas of interest. In our study, data from search task in digitally rendered 2D architectural plans have been explored and results indicated that irrespective of clustering technique, users fixated attention only 2 or 3 times for individual image. We have also presented GUI of a tool that can automatically identify areas of interest for any gaze tracking data sample using FCM or EM Algorithms.

Item Type:	Conference Paper
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to the Institute of Electrical and Electronics Engineers Inc.
Keywords:	Eye Gaze Tracker; Human Computer Interaction(HCI); Soft Clustering; Validation Metric; Visual Search Behaviour
Department/Centre:	Division of Mechanical Sciences > Centre for Product Design & Manufacturing
Date Deposited:	06 Jun 2022 06:43
Last Modified:	06 Jun 2022 06:44
URI:	https://eprints.iisc.ac.in/id/eprint/73231

Actions (login required)

View Item