Efficiency in Real-time Webcam Gaze Tracking

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

7 Citations (Scopus)
54 Downloads (Pure)

Abstract

Efficiency and ease of use are essential for practical applications of camera based eye/gaze-tracking. Gaze tracking involves estimating where a person is looking on a screen based on face images from a computer-facing camera. In this paper we investigate two complementary forms of efficiency in gaze tracking: 1. The computational efficiency of the system which is dominated by the inference speed of a CNN predicting gaze-vectors; 2. The usability efficiency which is determined by the tediousness of the mandatory calibration of the gaze-vector to a computer screen. To do so, we evaluate the computational speed/accuracy trade-off for the CNN and the calibration effort/accuracy trade-off for screen calibration. For the CNN, we evaluate the full face, two-eyes, and single eye input. For screen calibration, we measure the number of calibration points needed and evaluate three types of calibration: 1. pure geometry, 2. pure machine learning, and 3. hybrid geometric regression. Results suggest that a single eye input and geometric regression calibration achieve the best trade-off.
Original languageEnglish
Title of host publicationComputer Vision – ECCV 2020 Workshops
Subtitle of host publicationProceedings
EditorsAdrien Bartoli, Andrea Fusiello
Place of PublicationCham
PublisherSpringer
Chapter34
Pages529 - 543
Number of pages15
Edition1
ISBN (Electronic)978-3-030-66415-2
ISBN (Print)978-3-030-66414-5
DOIs
Publication statusPublished - 2020
EventEuropean Conference on Computer Vision (ECCV) 2020 Workshop on Eye Gaze in AR, VR, and in the Wild (OpenEyes) - Glassgow, United Kingdom
Duration: 23 Aug 202028 Aug 2020
https://openeyes-workshop.github.io/

Publication series

NamePart of the Lecture Notes in Computer Science book series (LNCS, volume 12535) Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 12535)
PublisherSpringer
Volume12535
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

WorkshopEuropean Conference on Computer Vision (ECCV) 2020 Workshop on Eye Gaze in AR, VR, and in the Wild (OpenEyes)
Abbreviated titleECCVW 2020; OpenEyes 2020
Country/TerritoryUnited Kingdom
CityGlassgow
Period23/08/2028/08/20
Internet address

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  • Best Paper Award

    Gudi, A.A. (Recipient), 23 Aug 2020

    Prize: Prize (including medals and awards)

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