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Attention meter: a vision-based input toolkit for interaction designers

Published: 21 April 2006 Publication History

Abstract

This paper shows how a software toolkit can allow graphic designers to make camera-based interactive environments in a short period of time without experience in user interface design or machine vision. The Attention Meter, a vision-based input toolkit, gives users an analysis of faces found in a given image stream, including facial expression, body motion, and attentive activities. This data is fed to a text file that can be easily understood by humans and programs alike. A four day workshop demonstrated that some Flash-savvy architecture students could construct interactive spaces (e.g. TaiKer-KTV and ScreamMarket) based on body and head motions.

References

[1]
Krueger, M., Gionfriddo, T., Hinrichsen, K., Videoplace- An Artificial Reality, in proceedings of CHI '85, pp.35--pp.40
[2]
Pashler, H., The Psychology of Attention. Bradford Books. Reprint edition, 1999
[3]
Selker, T., Visual Attentive Interfaces. In BT Technology Journal, Vol 22 No 4, (2004), 146--150.
[4]
Bonanni, L., Lee, C.H., Selker, T., Attention-Based Design of Augmented Reality Interfaces, Ext. Abstracts CHI 2005, ACM Press (2005).
[5]
Weiland, W., Stokes, J., Ryder, J., ScanEval - A toolkit for eye-tracking research and attention-driven applications, Human Factors and Ergonomics Society 42nd Annual Meeting, Chicago, IL 5-9 Oct. 1998.
[6]
Seeing Machines-faceLAB, seeingmachines.com
[7]
OpenCV- Intel Open Source Computer Vision Library, http://www.intel.com/
[8]
Adobe Flash, http://www.adobe.com/

Cited By

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  • (2020)Quantification of Users' Visual Attention During Everyday Mobile Device InteractionsProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376449(1-14)Online publication date: 21-Apr-2020
  • (2016)A Visual Attention Monitor Based on Steady-State Visual Evoked PotentialIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2015.250137824:3(399-408)Online publication date: Mar-2016
  • (2014)Mitigating problems in video-mediated group discussionsProceedings of the 2014 workshop on Understanding and Modeling Multiparty, Multimodal Interactions10.1145/2666242.2666247(39-44)Online publication date: 16-Nov-2014
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      cover image ACM Conferences
      CHI EA '06: CHI '06 Extended Abstracts on Human Factors in Computing Systems
      April 2006
      1914 pages
      ISBN:1595932984
      DOI:10.1145/1125451
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

      Publication History

      Published: 21 April 2006

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      Author Tags

      1. interactivity
      2. multimodal interaction
      3. visual attention

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      CHI06
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      CHI06: CHI 2006 Conference on Human Factors in Computing Systems
      April 22 - 27, 2006
      Québec, Montréal, Canada

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      Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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      Cited By

      View all
      • (2020)Quantification of Users' Visual Attention During Everyday Mobile Device InteractionsProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376449(1-14)Online publication date: 21-Apr-2020
      • (2016)A Visual Attention Monitor Based on Steady-State Visual Evoked PotentialIEEE Transactions on Neural Systems and Rehabilitation Engineering10.1109/TNSRE.2015.250137824:3(399-408)Online publication date: Mar-2016
      • (2014)Mitigating problems in video-mediated group discussionsProceedings of the 2014 workshop on Understanding and Modeling Multiparty, Multimodal Interactions10.1145/2666242.2666247(39-44)Online publication date: 16-Nov-2014
      • (2014)An adaptive graphical user interface based on attention level and diameter of eye pupil2014 IEEE 6th International Conference on Adaptive Science & Technology (ICAST)10.1109/ICASTECH.2014.7068126(1-4)Online publication date: Oct-2014
      • (2014)Design recommendations for camera-based head-controlled interfaces that replace the mouse for motion-impaired usersUniversal Access in the Information Society10.1007/s10209-013-0326-z13:4(471-482)Online publication date: 1-Nov-2014
      • (2011)Understanding Considerate Systems - UCS (PronouncedProceedings of the 2011 International Conference on Technologies and Applications of Artificial Intelligence10.1109/TAAI.2011.67(1-12)Online publication date: 11-Nov-2011
      • (2010)Understanding considerate systems — UCS (pronounced: You see us)2010 International Symposium on Collaborative Technologies and Systems10.1109/CTS.2010.5478532(1-12)Online publication date: May-2010
      • (2009)PAD-based multimodal affective fusion2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops10.1109/ACII.2009.5349552(1-8)Online publication date: Sep-2009
      • (2006)Attentive Person Selection for Human-Robot InteractionIntelligent Computing in Signal Processing and Pattern Recognition10.1007/978-3-540-37258-5_83(728-734)Online publication date: 2006

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