—Understanding the effect of blur is an important problem in unconstrained visual analysis. We address this problem in the context of image-based recognition, by a fusion of imag...
Raghuraman Gopalan, Sima Taheri, Pavan K. Turaga, ...
We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating feature...
This paper presents a technique for face recognition which uses wavelet transform to derive desirable facial features. Three level decompositions are used to form the pyramidal mul...
Dattatray V. Jadhav, Jayant V. Kulkarni, Raghunath...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
Wen-Sheng Vincent Chu, Ju-Chin Chen, Jenn-Jier Jam...