Paper Info
Title
Variant Pose Face Recognition Using Discrete Wavelet Transform And Linear Regression
Abstract
Face recognition in constraint conditions is no longer a further challenge. However, even the best method is not able to cope with real world situations. In this paper, a robust method is proposed such that the performance of the face recognition system is still highly reliable even if the face undergoes large head rotation. Our proposed method considers local regions from half side of face rather than using the holistic face approach since in the former approach the "linearity" of features within the limited region is somewhat preserved regardless of the pose variation. Discrete wavelet transform is then utilized onto these patches in order to form face feature vectors. We train our recognizer using linear regression algorithm to interpret the relationship between a face vector for a specific pose and its corresponding frontal face feature vector. We demonstrate that our proposed method is able to recognize a non-frontal face with high accuracy even under low-resolution image by relying only on single frontal face in the database.
Year
DOI
Venue
2012
10.1142/S0218001412560137
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Pose, patch, discrete wavelet transform, face feature vector, linear regression, low-resolution
Computer vision,Facial recognition system,Feature vector,Pattern recognition,Computer science,Linearity,Large head,Discrete wavelet transform,Artificial intelligence,Linear regression
Journal
Volume
Issue
ISSN
26
6
0218-0014
Citations 
PageRank 
References 
2
0.36
32
Authors
2
Name
Order
Citations
PageRank
Seyed Omid Shahdi151.48
Syed Abdul Rahman Abu-Bakar2162.74