research-article

Detecting eye contact using wearable eye-tracking glasses

Authors:

Gregory D. Abowd,

James M. RehgAuthors Info & Claims

UbiComp '12: Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Pages 699 - 704

https://doi.org/10.1145/2370216.2370368

Published: 05 September 2012 Publication History

Abstract

We describe a system for detecting moments of eye contact between an adult and a child, based on a single pair of gaze-tracking glasses which are worn by the adult. Our method utilizes commercial gaze tracking technology to determine the adult's point of gaze, and combines this with computer vision analysis of video of the child's face to determine their gaze direction. Eye contact is then detected as the event of simultaneous, mutual looking at faces by the dyad. We report encouraging findings from an initial implementation and evaluation of this approach.

References

[1]

O. Aghazadeh, J. Sullivan, and S. Carlsson. Novelty detection from an ego-centric perspective. In CVPR, 2011.

Digital Library

[2]

L. Breiman. Random forests. Mach. Learn., 45(1):5--32, Oct. 2001.

Digital Library

[3]

A. Bulling and D. Roggen. Recognition of visual memory recall processes using eye movement analysis. In UbiComp, 2011.

Digital Library

[4]

A. Bulling, J. A. Ward, H. Gellersen, and G. Troster. Robust recognition of reading activity in transit using wearable electrooculography. In Pervasive Computing, 2008.

Digital Library

[5]

K. Chawarska and F. Shic. Looking but not seeing: Atypical visual scanning and recognition of faces in 2 and 4-year-old children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 39:1663--1672, 2009.

[6]

G. Dawson, K. Toth, R. Abbott, J. Osterling, J. Munson, A. Estes, and J. Liaw. Early social attention impairments in autism: Social orienting, joint attention, and attention to distress. Developmental Psychology, 40(2):271--283, 2004.

[7]

W. Einhauser, M. Spain, and P. Perona. Objects predict fixations better than early saliency. In Journal of Vision, 2008.

[8]

A. Fathi, A. Farhadi, and J. M. Rehg. Understanding egocentric activities. In ICCV, 2011.

Digital Library

[9]

A. Fathi, J. K. Hodgins, and J. M. Rehg. Social interactions: A first-person perspective. In CVPR, 2012.

Digital Library

[10]

A. Fathi, X. Ren, and J. M. Rehg. Learning to recognize objects in egocentric activities. In CVPR, 2011.

Digital Library

[11]

J. M. Franchak, K. S. Kretch, K. C. Soska, J. S. Babcock, and K. E. Adolph. Head-mounted eye-tracking of infants' natural interactions: a new method. In Proceedings of the 2010 Symposium on Eye-Tracking Research and Applications, ETRA '10, pages 21--27, 2010.

Digital Library

[12]

J. Guo and G. Feng. How eye gaze feedback changes parent-child joint attention in shared storybook reading? an eye-tracking intervention study. In 2nd Workshop on Eye Gaze in Intelligent Human Machine Interaction, 2011.

[13]

D. W. Hansen and Q. Ji. In the eye of the beholder: A survey of models for eyes and gaze. PAMI, 32(3):478--500, Mar. 2010.

Digital Library

[14]

W. Jones, K. Carr, and A. Klin. Absence of preferential looking to the eyes of approaching adults predicts level of social disability in 2-year-old toddlers with autism spectrum disorder. Archives of General Psychiatry, 65(8):946--954, 2008.

[15]

K. M. Kitani, T. Okabe, Y. Sato, and A. Sugimoto. Fast unsupervised ego-action learning for first-person sports videos. In CVPR, 2011.

Digital Library

[16]

A. Klin, W. Jones, R. Schultz, F. Volkmar, and D. Cohen. Visual fixation patterns during viewing of naturalistic social situations as predictors of social competence in individuals with autism. In Archives of General Psychiatry, 2002.

[17]

M. F. Land and M. Hayhoe. In what ways do eye movements contribute to everyday activities? Vision Research, 41:3559--3565, 2001.

[18]

Y. J. Lee, J. Ghosh, and K. Grauman. Discovering important people and objects for egocentric video summarization. In CVPR, 2012.

Digital Library

[19]

S. R. Leekam, B. Lopez, and C. Moore. Attention and joint attention in preschool children with autism. Developmental Psychology, 36(2):261--273, 2000.

[20]

A. Liu and D. Salvucci. Modeling and prediction of human driver behavior. In HCI, 2001.

[21]

D. Model and M. Eizenman. A probabilistic approach for the estimation of angle kappa in infants. In Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA '12, pages 53--58, 2012.

Digital Library

[22]

B. Noris, M. Barker, J. Nadel, F. Hentsch, F. Ansermet, and A. Billard. Measuring gaze of children with autism spectrum disorders in naturalistic interactions. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pages 5356--5359, 30 2011-sept. 3 2011.

[23]

J. B. Pelz and R. Consa. Oculomotor behavior and perceptual strategies in complex tasks. In Vision Research, 2001.

[24]

L. Piccardi, B. Noris, O. Barbey, A. Billard, F. Keller, and et al. Wearcam: A head mounted wireless camera for monitoring gaze attention and for the diagnosis of developmental disorders in young children. In 16th IEEE International Simposium on Robot and Human Interactive Communication, 2007.

[25]

H. Pirsiavash and D. Ramanan. Detecting activities of daily living in first-person camera views. In CVPR, 2012.

Digital Library

[26]

X. Ren and C. Gu. Figure-ground segmentation improves handled object recognition in egocentric video. In CVPR, 2010.

[27]

B. Schiele, N. Oliver, T. Jebara, and A. Pentland. An interactive computer vision system - dypers: dynamic personal enhanced reality system. In ICVS, 1999.

Digital Library

[28]

R. Schleicher, N. Galley, S. Briest, and L. Galley. Blinks and saccades are indicators of fatigue in sleepiness warnings: looking tired? In Ergonomics, 2008.

[29]

A. Senju and M. H. Johnson. Atypical eye contact in autism: models, mechanisms and development. Neuroscience and biobehavioral reviews, 33(8):1204--1214, 2009.

[30]

J. Skotte, J. Nojgaard, L. Jorgensen, K. Christensen, and G. Sjogaard. Eye blink frequency during different computer tasks quantified by electrooculography. In European Journal of Applied Physiology, 2007.

[31]

E. H. Spriggs, F. D. L. Torre, and M. Hebert. Temporal segmentation and activity classification from first-person sensing. In Egovision Workshop, 2009.

[32]

E. Stuyven, K. V. der Goten, A. Vandierendonck, K. Claeys, and L. Crevits. The effect of cognitive load on saccadic eye movements. In Acta Psychologica, 2000.

[33]

B. W. Tatler, M. M. Hayhoe, M. F. Land, and D. H. Ballard. Eye guidance in natural vision: reinterpreting salience. In Journal of Vision, 2011.

[34]

A. M. Wetherby, N. Watt, L. Morgan, and S. Shumway. Social communication profiles of children with autism spectrum disorders late in the second year of life. In Journal of Autism and Developmental Disorders, 2007.

[35]

W. Yi and D. Ballard. Recognizing behavior in hand-eye coordination patterns. In International Journal of Humanoid Robots, 2009.

[36]

L. Zwaigenbaum, S. E. Bryson, T. Rogers, W. Roberts, J. Brian, and P. Szatmari. Behavioral manifestations of autism in the first year of life. In International Journal of Developmental Neuroscience, 2005.

Cited By

Hooge INuthmann ANyström MNiehorster DHolleman GAndersson RHessels R(2025)The fundamentals of eye tracking part 2: From research question to operationalizationBehavior Research Methods10.3758/s13428-024-02590-257:2Online publication date: 24-Jan-2025
https://doi.org/10.3758/s13428-024-02590-2
Ma FHe YSun BLi SCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Less is More: Adaptive Feature Selection and Fusion for Eye Contact DetectionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3688987(11390-11396)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3688987
Li KZhang RChen BChen SYin SMahmud SLiang QGuimbretiere FZhang CGanesan DShi W(2024)GazeTrak: Exploring Acoustic-based Eye Tracking on a Glass FrameProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3649376(497-512)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3636534.3649376
Show More Cited By

Index Terms

Detecting eye contact using wearable eye-tracking glasses
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

UbiComp '12: Proceedings of the 2012 ACM Conference on Ubiquitous Computing

September 2012

1268 pages

ISBN:9781450312240

DOI:10.1145/2370216

General Chair:
Anind K. Dey
Carnegie Mellon University
,
Program Chairs:
Hao-Hua Chu
National Taiwan University, Taiwan
,
Gillian Hayes
University of California, Irvine

Copyright © 2012 ACM.

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Published: 05 September 2012

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Ubicomp '12

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Ubicomp '12: The 2012 ACM Conference on Ubiquitous Computing

September 5 - 8, 2012

Pennsylvania, Pittsburgh

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UbiComp '12 Paper Acceptance Rate 58 of 301 submissions, 19%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Hooge INuthmann ANyström MNiehorster DHolleman GAndersson RHessels R(2025)The fundamentals of eye tracking part 2: From research question to operationalizationBehavior Research Methods10.3758/s13428-024-02590-257:2Online publication date: 24-Jan-2025
https://doi.org/10.3758/s13428-024-02590-2
Ma FHe YSun BLi SCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Less is More: Adaptive Feature Selection and Fusion for Eye Contact DetectionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3688987(11390-11396)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3688987
Li KZhang RChen BChen SYin SMahmud SLiang QGuimbretiere FZhang CGanesan DShi W(2024)GazeTrak: Exploring Acoustic-based Eye Tracking on a Glass FrameProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3649376(497-512)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3636534.3649376
Hempel TJung MAbdelrahman AAl-Hamadi A(2024)NITEC: Versatile Hand-Annotated Eye Contact Dataset for Ego-Vision Interaction2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00438(4425-4434)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00438
Ren XFan JXu NWang SDong CWen Z(2024) DPGazeSynthInformation Sciences: an International Journal10.1016/j.ins.2024.120720675:COnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.ins.2024.120720
Ahn YChoi HChoi RAhn SKim B(2024)BIM-based augmented reality navigation for indoor emergency evacuationExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124469255:PAOnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124469
Wu XLi LZhu HZhou GLi LSu FHe SWang YLong X(2024)EG-Net: Appearance-based eye gaze estimation using an efficient gaze network with attention mechanismExpert Systems with Applications10.1016/j.eswa.2023.122363238(122363)Online publication date: Mar-2024
https://doi.org/10.1016/j.eswa.2023.122363
Plizzari CGoletto GFurnari ABansal SRagusa FFarinella GDamen DTommasi T(2024)An Outlook into the Future of Egocentric VisionInternational Journal of Computer Vision10.1007/s11263-024-02095-7132:11(4880-4936)Online publication date: 28-May-2024
https://doi.org/10.1007/s11263-024-02095-7
Boyd LBoyd L(2024)From Sensory Perception to Realtime NonVerbal CommunicationThe Sensory Accommodation Framework for Technology10.1007/978-3-031-48843-6_6(85-99)Online publication date: 2-Jan-2024
https://doi.org/10.1007/978-3-031-48843-6_6
Li QWang PLiu CLi XHou J(2024)Integration patterns in the use of metadata for data sense‐making during relevance evaluation: An interpretable deep learning‐based predictionJournal of the Association for Information Science and Technology10.1002/asi.24961Online publication date: 29-Oct-2024
https://doi.org/10.1002/asi.24961
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