Class Specific Threshold Selection in Face Space Using Set Estimation Technique for RGB Color Components

Authors:
Madhura Datta;C. A. Murthy
Affiliations:
UGC-Academic Staff College, University of Calcutta, Kolkata, India 700 009;Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India 700 108
Venue:
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Year:
2009

Citing 2
Cited 1

Face recognition: A literature survey

ACM Computing Surveys (CSUR)
Eigenspace-based face recognition: a comparative study of different approaches

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

Two dimensional synthetic face generation and verification using set estimation technique

Computer Vision and Image Understanding

Quantified Score

Hi-index	0.02

Visualization

Abstract

In conventional face recognition techniques, any query image is always classified to one of the face classes irrespective of whether the query image is a face or not. Most of the recognition algorithms are dissimilarity based, and one needs to put a proper threshold on the dissimilarity value for the sake of classification. In this paper, we have introduced a novel thresholding technique for classification, where the query image is not necessarily classified to one of the classes in the training set. The theoretical formulation of the thresholding technique and its utility are demonstrated on color face and non face datasets with RGB color components as features in the subspace. The proposed threshold selection is based on statistical method of set estimation and is guided by minimal spanning tree. Experiment shows that the proposed class specific threshold based technique performs better than the non threshold based systems using subspace algorithms.