Share Email Print
cover

Proceedings Paper

Reinforced adaboost face detector using support vector machine
Author(s): Jaeyoon Jang; Yunkoo C.; Jaehong K.; Hosub Yoon
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We propose a novel face detection algorithm in order to improve higher detection rate of face-detector than conventional haar - adaboost face detector. Our purposed method not only improves detection rate of a face but decreases the number of false-positive component. In order to get improved detection ability, we merged two classifiers: adaboost and support vector machine. Because SVM and Adaboost use different feature, they are complementary each other. We can get 2~4% improved performance using proposed method than previous our detector that is not applied proposed method. This method makes improved detector that shows better performance without algorithm replacement.

Paper Details

Date Published: 22 August 2014
PDF: 6 pages
Proc. SPIE 9286, Second International Conference on Applications of Optics and Photonics, 92864W (22 August 2014); doi: 10.1117/12.2064815
Show Author Affiliations
Jaeyoon Jang, Korea Univ. of Science and Technology (Korea, Republic of)
Yunkoo C., Electronics and Telecommunications Research Institute (Korea, Republic of)
Jaehong K., Electronics and Telecommunications Research Institute (Korea, Republic of)
Hosub Yoon, Electronics and Telecommunications Research Institute (Korea, Republic of)


Published in SPIE Proceedings Vol. 9286:
Second International Conference on Applications of Optics and Photonics
Manuel Filipe P. C. Martins Costa; Rogério Nunes Nogueira, Editor(s)

© SPIE. Terms of Use
Back to Top