A pose adaptive eye detection method using 3D face information

Hyunjun Kim, Jinsu Kim, Jaihie Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes an eye detection algorithm robust to head pose variation. First, face region is detected by Viola-Jones algorithm. Second, in order to detect eye robust to pose variation, a window template is generated from the 3D mean face model. Finally, eye is detected and localized by using this window template. In the experiments, the proposed method is tested on CAS-PEAL database.

Original languageEnglish
Title of host publication13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479939428
DOIs
Publication statusPublished - 2014 Sep 30
Event13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Kota Kinabalu, Malaysia
Duration: 2014 Jan 152014 Jan 18

Publication series

Name13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings

Other

Other13th International Conference on Electronics, Information, and Communication, ICEIC 2014
CountryMalaysia
CityKota Kinabalu
Period14/1/1514/1/18

Fingerprint

Experiments

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Kim, H., Kim, J., & Kim, J. (2014). A pose adaptive eye detection method using 3D face information. In 13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings [6914360] (13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ELINFOCOM.2014.6914360
Kim, Hyunjun ; Kim, Jinsu ; Kim, Jaihie. / A pose adaptive eye detection method using 3D face information. 13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. (13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings).
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abstract = "This paper proposes an eye detection algorithm robust to head pose variation. First, face region is detected by Viola-Jones algorithm. Second, in order to detect eye robust to pose variation, a window template is generated from the 3D mean face model. Finally, eye is detected and localized by using this window template. In the experiments, the proposed method is tested on CAS-PEAL database.",
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Kim, H, Kim, J & Kim, J 2014, A pose adaptive eye detection method using 3D face information. in 13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings., 6914360, 13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 13th International Conference on Electronics, Information, and Communication, ICEIC 2014, Kota Kinabalu, Malaysia, 14/1/15. https://doi.org/10.1109/ELINFOCOM.2014.6914360

A pose adaptive eye detection method using 3D face information. / Kim, Hyunjun; Kim, Jinsu; Kim, Jaihie.

13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 6914360 (13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This paper proposes an eye detection algorithm robust to head pose variation. First, face region is detected by Viola-Jones algorithm. Second, in order to detect eye robust to pose variation, a window template is generated from the 3D mean face model. Finally, eye is detected and localized by using this window template. In the experiments, the proposed method is tested on CAS-PEAL database.

AB - This paper proposes an eye detection algorithm robust to head pose variation. First, face region is detected by Viola-Jones algorithm. Second, in order to detect eye robust to pose variation, a window template is generated from the 3D mean face model. Finally, eye is detected and localized by using this window template. In the experiments, the proposed method is tested on CAS-PEAL database.

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Kim H, Kim J, Kim J. A pose adaptive eye detection method using 3D face information. In 13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. 6914360. (13th International Conference on Electronics, Information, and Communication, ICEIC 2014 - Proceedings). https://doi.org/10.1109/ELINFOCOM.2014.6914360