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ICCV
2005
IEEE
16 years 1 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
131
Voted
PAMI
2012
13 years 2 months ago
Trainable Convolution Filters and Their Application to Face Recognition
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...
ICCV
2001
IEEE
16 years 1 months ago
A Gabor Feature Classifier for Face Recognition
This paper describes a novel Gabor Feature Class$er (GFC)method forface recognition. The GFC method employs an enhanced Fisher discrimination model on an augmented Gabor feature v...
Chengjun Liu, Harry Wechsler
113
Voted
ACCV
2010
Springer
14 years 6 months ago
Randomised Manifold Forests for Principal Angle-Based Face Recognition
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
Ujwal D. Bonde, Tae-Kyun Kim, K. R. Ramakrishnan
CVPR
2009
IEEE
16 years 6 months ago
Volterrafaces: Discriminant Analysis using Volterra Kernels
In this paper we present a novel face classification system where we represent face images as a spatial arrangement of image patches, and seek a smooth non-linear functional map...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri