Using Edge Orientation Histograms in Face--based Gender Classification

Beitrag bei einer Tagung
(Originalarbeit)


Details zur Publikation

Autorinnen und Autoren: Timotius I, Setyawan I
Jahr der Veröffentlichung: 2014
Tagungsband: International Conference on Information Technology Systems and Innovation
Seitenbereich: 93 - 98
Sprache: Englisch


Abstract


In this paper we present our evaluation of the Edge Orientation Histograms (EOH) as feature descriptors in an automatic face-based gender classification application. The feature descriptors extracted from an input image are evaluated using estimated arithmetic means of accuracies to select the feature descriptors that play the most important role in classification success. Our experiments show that features corresponding to the jawline of the subject play the most important role, yielding an average classification accuracy of up to 86%.



FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Timotius, Ivanna
Lehrstuhl für Informatik 5 (Mustererkennung)


Zitierweisen

APA:
Timotius, I., & Setyawan, I. (2014). Using Edge Orientation Histograms in Face--based Gender Classification. In International Conference on Information Technology Systems and Innovation (pp. 93 - 98). Bandung, ID.

MLA:
Timotius, Ivanna, and Iwan Setyawan. "Using Edge Orientation Histograms in Face--based Gender Classification." Proceedings of the International Conference on Information Technology Systems and Innovation, Bandung 2014. 93 - 98.

BibTeX: 

Zuletzt aktualisiert 2018-20-10 um 20:10