Estimation of viewer's response for contextual understanding of tasks using features of eye-movements

Eye Tracking Research and Applications Symposium (ETRA)

Volumn , Issue , 2010, Pages 53-56

  Nakayama, Minoru ^a   Hayashi, Yuko ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Answer correctness; Discriminant analysis; Eye movement metrics; Eye movements; User's response estimation

Indexed keywords

CONTEXTUAL UNDERSTANDING; DIRECTIONAL FEATURE; ESTIMATION PERFORMANCE; EYE-MOVEMENT METRICS; TWO DIMENSIONAL SPACES;

DISCRIMINANT ANALYSIS; ESTIMATION;

EYE MOVEMENTS;

EID: 77952408978     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1743666.1743678     Document Type: Conference Paper

References (15)

1. CHANG, C., AND LIN, C., 2008. Libsvm: A library for support vector machines (last updated: May 13, 2008). Available 21 July 2009 at URL: http://www.csie.ntu.edu.tw /~cjlin/libsvm.
2. DUCHOWSKI, A. T., 2006. High-level eye movement metrics in the usability context. Position paper, CHI2006Workshop: Getting a Measure of Satisfaction from Eyetracking in Practice.
3. EBISAWA, Y., AND SUGIURA, M. 1998. Influences of target and fixation point conditions on characteristics of visually guided voluntary saccade. The Journal of the Institute of Image Information and Television Engineers 52, 11, 1730-1737.
4. EHMKE, C., AND WILSON, S. 2007. Identifying web usability problems from eye-tracking. In Proceedings of HCI 2007, British Computer Society, L. Ball, M. Sasse, C. Sas, T. Ormerod, A. Dix, P. Bagnall, and T. McEwan, Eds.
5. FAWCETT, T. 2006. An introduction to roc analysis. Pattern Recognition Letters 27, 861-874.
6. JACOB, R. J. K., AND KARN, K. S. 2003. Eye tracking in human- computer interaction and usability research: Ready to deliver the promises. In The Mind's Eye: Cognitive and Applied Aspects of Eye Movement Research, Hyona, Radach, and Deubel, Eds. Elsevier Science BV, Oxford, UK.
7. NAKAMICHI, N., SHIMA, K., SAKAI, M., AND ICHI MATSUMOTO, K. 2006. Detecting low usability web pages using quantitative data of users' behavior. In Proceedings of the 28th International Conference on Software Engineering (ICSE'06), ACM Press.
8. NAKAYAMA, M., AND HAYASHI, Y. 2009. Feasibility study for the use of eye-movements in estimation of answer correctness. In Proceedings of COGAIN2009, A. Villanueva, J. P. Hansen, and B. K. Ersboell, Eds., 71-75.
9. NAKAYAMA, M., AND SHIMIZU, Y. 2004. Frequency analysis of task evoked pupillary response and eye-movement. In Eye Tracking Research and Applications Symposium 2002, ACM Press, New York, USA, S. N. Spencer, Ed., ACM, 71-76.
10. NAKAYAMA, M., AND TAKAHASI, Y. 2008. Estimation of certainty for responses to multiple-choice questionnaires using eye movements. ACM TOMCCAP 5, 2, Article 14.
11. PUOLÄMAKI, Y., SALOJÄRVI, J., SAVIA, E., SIMOLA, J., AND KASKI, S. 2005. Combining eye movements and collaborative filtering for proactive information retrieval. In Proceedings of ACM-SIGIR 2005, ACM Press, New York, USA, A. Heikkil, A. Pietik, and O. Silven, Eds., ACM, 145-153.
12. RAYNER, K. 1998. Eye movements in reading and information processing: 20 years of research. Psychological Bulletin 124, 3, 372-422.
13. STORK, D. G. R., DUDA, O., AND HART, P. E. 2001. Pattern Classification, 2nd ed. JohnWiley & Sons, Inc. Japanese translation by M. Onoue, New Technology Communications Co., Ltd., Tokyo, Japan (2001).
14. TATLER, B. W., WADE, N. J., AND KAULARD, K. 2007. Examining art: dissociating pattern and perceptual influences on oculomotor behaviour. Spatial Vision 21, 1-2, 165-184.
15. TATLER, B. W. 2007. The central fixation bias in scene viewing: Selecting and optimal viewing position independently of motor biases and image feature distributions. Journal of Vision 7, 14, 1-17.