Graph-based clustering for identifying region of interest in eye tracker data analysis

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He, Kanghang and Yang, Cheng and Stankovic, Vladimir and Stankovic, Lina; (2017) Graph-based clustering for identifying region of interest in eye tracker data analysis. In: 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP). IEEE, GBR. ISBN 9781509036509 (https://doi.org/10.1109/MMSP.2017.8122264)

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Abstract

Localization of a viewer's region of interest (ROI) on eye gaze signal trajectories acquired by eye trackers is a widely used approach in scene analysis, image compression, and quality of experience assessment. In this paper, we propose a novel clustering approach for ROI estimation from potentially noisy raw eye gaze data, based on signal processing on graphs. The clustering approach adapts graph signal processing (GSP)-based classification by first cleverly selecting a starting data sample, and then classifying the remaining samples. Furthermore, Graph Fourier Transform is used to adjust GSP parameters on-the-fly to maximise accuracy. Experimental results show competitive clustering accuracy of our proposed scheme compared to Density-based spatial clustering of applications with noise (DB-SCAN), Distance-Threshold Identification (I-DT), and Mean-Shift on publicly available Shape Dataset and the potential of estimating ROI accurately on true eye tracker data.

ORCID iDs

He, Kanghang ORCID logoORCID: https://orcid.org/0000-0001-8251-7991, Yang, Cheng ORCID logoORCID: https://orcid.org/0000-0002-3540-1598, Stankovic, Vladimir ORCID logoORCID: https://orcid.org/0000-0002-1075-2420 and Stankovic, Lina ORCID logoORCID: https://orcid.org/0000-0002-8112-1976;
  • Item type:Book Section
    ID code:63025
    Dates:
    Date
    Event
    1 December 2017
    Published
    21 June 2017
    Accepted
    Notes:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:24 Jan 2018 16:43
    Last modified:18 Dec 2024 01:07
    URI:https://strathprints.strath.ac.uk/id/eprint/63025
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