Facial features extraction by accelerated implementation of circular hough transform and appearance evaluation

Hayato Iwasa, Wataru Oyama, Tetsushi Wakabayashi, Fumitaka Kimura

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

1 Citation (Scopus)

Abstract

Extraction of facial feature points is essential task for many kinds of applications of face images. The feasibility of facial features extraction is determined by not only its accuracy but processing time. Some applications require real-time detection of facial features. This research aims to propose a method of facial features extraction by an accelerated implementation of circular Hough transform with gradients and appearance evaluation by histogram of gradient features. The acceleration implementation employs General Purpose computing on Graphics Processing Unit. Experiment using FERET database shows that the proposed method successfully extracted eyes and nose for 98.44% and 99.50% of frontal face images in the dataset. And 96.5% of computational time was reduced by accelerated implementation employing GPGPU.

Original languageEnglish
Title of host publication2015 Frontiers of Computer Vision, FCV 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479917204
DOIs
Publication statusPublished - Jan 1 2015
Externally publishedYes
Event2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2015 - Mokpo, Korea, Republic of
Duration: Jan 28 2015Jan 30 2015

Other

Other2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2015
CountryKorea, Republic of
CityMokpo
Period1/28/151/30/15

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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    Iwasa, H., Oyama, W., Wakabayashi, T., & Kimura, F. (2015). Facial features extraction by accelerated implementation of circular hough transform and appearance evaluation. In 2015 Frontiers of Computer Vision, FCV 2015 [7103709] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FCV.2015.7103709