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» On Deep Generative Models with Applications to Recognition
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AVSS
2009
IEEE
14 years 3 months ago
A 3D Face Model for Pose and Illumination Invariant Face Recognition
Generative 3D face models are a powerful tool in computer vision. They provide pose and illumination invariance by modeling the space of 3D faces and the imaging process. The powe...
Pascal Paysan, Reinhard Knothe, Brian Amberg, Sami...
IPCV
2010
13 years 6 months ago
Video Action Recognition Using Residual Vector Quantization and Hidden Markov Models
In this paper, we discuss usage of a multi-stage Residual Vector Quantization (RVQ) strategy for human action recognition. To the best of our knowledge, this is the first reported...
Salman Aslam, Christopher F. Barnes, Aaron F. Bobi...
WCE
2007
13 years 9 months ago
Reconstruction of 3D Solid Models Using Fuzzy Logic Recognition
—This paper presents an application of fuzzy logic theory to the reconstruction of solid models from engineering drawings. In engineering drawing, two-dimensional (2D) orthograph...
Zhe Wang, Mohammed Latif
ICCV
2001
IEEE
14 years 10 months ago
Combining Single View Recognition and Multiple View Stereo for Architectural Scenes
This paper describes a structure from motion and recognition paradigm for generating 3D models from 2D sets of images. In particular we consider the domain of architectural photog...
Anthony R. Dick, Philip H. S. Torr, Simon J. Ruffl...
IJON
1998
102views more  IJON 1998»
13 years 8 months ago
Developments of the generative topographic mapping
The Generative Topographic Mapping (GTM) model was introduced by 7) as a probabilistic re-formulation of the self-organizing map (SOM). It offers a number of advantages compared ...
Christopher M. Bishop, Markus Svensén, Chri...