Evaluation of Edge Orientation Histograms in Smile Detection

Beitrag bei einer Tagung
(Originalarbeit)


Details zur Publikation

Autorinnen und Autoren: Timotius I, Setyawan I
Verlag: IEEE
Jahr der Veröffentlichung: 2014
Tagungsband: The 6th International Conference on Information Technology and Electrical Engineering (ICITEE 2014)
Seitenbereich: 1 - 5
ISBN: 978-1-4799-5302-8
Sprache: Englisch


Abstract


Smile detection received a enormous attention due to its famous application as a `smile shutter' in digital cameras. Edge Orientation Histograms (EOH) is one of the possible feature descriptors in a smile detector. This paper presents an evaluation of the use of Edge Orientation Histograms in a lip image based smile detector. The system built in this paper aims to discriminate lip images depicting a smile (including thin smile and broad smile) from lip images depicting non-smiling expressions. By dividing the lip images into 2 × 4 cells, and using 5° histogram bin size, we achieved 87.8% arithmetic means of accuracies. The experiments show that it is recommended not to use spatial binning that is too small. However, it is recommended to use fine orientation binning. Finally, it is recommended to use all orientation bins as features.



FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Timotius, Ivanna
Lehrstuhl für Informatik 5 (Mustererkennung)


Zitierweisen

APA:
Timotius, I., & Setyawan, I. (2014). Evaluation of Edge Orientation Histograms in Smile Detection. In The 6th International Conference on Information Technology and Electrical Engineering (ICITEE 2014) (pp. 1 - 5). Yogyakarta, ID: IEEE.

MLA:
Timotius, Ivanna, and Iwan Setyawan. "Evaluation of Edge Orientation Histograms in Smile Detection." Proceedings of the The 6th International Conference on Information Technology and Electrical Engineering (ICITEE 2014), Yogyakarta IEEE, 2014. 1 - 5.

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Zuletzt aktualisiert 2018-21-10 um 08:00