Sciweavers

CVPR
2007
IEEE
13 years 11 months ago
Fisher Kernels on Visual Vocabularies for Image Categorization
Within the field of pattern classification, the Fisher kernel is a powerful framework which combines the strengths of generative and discriminative approaches. The idea is to ch...
Florent Perronnin, Christopher R. Dance
CVPR
2007
IEEE
13 years 11 months ago
Learning Generative Models via Discriminative Approaches
Generative model learning is one of the key problems in machine learning and computer vision. Currently the use of generative models is limited due to the difficulty in effective...
Zhuowen Tu
ICDAR
2009
IEEE
13 years 11 months ago
Fisher Kernels for Handwritten Word-spotting
The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to a...
Florent Perronnin, José A. Rodríguez...
CVPR
2010
IEEE
14 years 18 days ago
A Globally Optimal Data-Driven Approach for Image Distortion Estimation
Image alignment in the presence of non-rigid distortions is a challenging task. Typically, this involves estimating the parameters of a dense deformation field that warps a disto...
Yuandong Tian, Srinivasa Narasimhan
ICPR
2004
IEEE
14 years 5 months ago
Two-Stage Classification System combining Model-Based and Discriminative Approaches
For the tasks of classification, two types of patterns can generate problems: ambiguous patterns and outliers. Furthermore, it is possible to separate classification algorithms in...
Jonathan Milgram, Mohamed Cheriet, Robert Sabourin
ICPR
2006
IEEE
14 years 5 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum
ICPR
2008
IEEE
14 years 5 months ago
SVMs, Gaussian mixtures, and their generative/discriminative fusion
We present a new technique that employs support vector machines and Gaussian mixture densities to create a generative/discriminative joint classifier. In the past, several approac...
Georg Heigold, Hermann Ney, Thomas Deselaers
ICCV
2005
IEEE
14 years 6 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
ICCV
2005
IEEE
14 years 6 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
CVPR
2008
IEEE
14 years 6 months ago
Context and observation driven latent variable model for human pose estimation
Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human...
Abhinav Gupta, Trista Chen, Francine Chen, Don Kim...