Face recognition using reinforcement learning

Mehrtash T. Harandi, Majid Nili Ahmadabadi, Babak N. Araabi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

14 Citations (Scopus)

Abstract

Neuroscientists believe that human beings recognize faces not only by utilizing some holistic search among all learned faces, but also through a feature analysis that aimed to specify more important features of each specific face. In this paper, we propose a hierarchical classifier that uses both holistic search and per face dominant feature analysis to recognize faces. Reinforcement learning is used to find a set of dominant features for each image in a training dataset. Wavelet transform is employed as a preprocessing tool, which results in higher discrimination among classes. Simulation studies justify the better performance of the proposed method as compared to that of eigenface method.

Original languageEnglish
Title of host publication2004 International Conference on Image Processing, ICIP 2004
Pages2709-2712
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2004
Event2004 International Conference on Image Processing, ICIP 2004 - , Singapore
Duration: 18 Oct 200421 Oct 2004

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume4
ISSN (Print)1522-4880

Conference

Conference2004 International Conference on Image Processing, ICIP 2004
CountrySingapore
Period18/10/0421/10/04

Cite this

Harandi, M. T., Ahmadabadi, M. N., & Araabi, B. N. (2004). Face recognition using reinforcement learning. In 2004 International Conference on Image Processing, ICIP 2004 (pp. 2709-2712). (Proceedings - International Conference on Image Processing, ICIP; Vol. 4). https://doi.org/10.1109/ICIP.2004.1421663