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» Face Recognition Using Active Appearance Models
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CVPR
2012
IEEE
13 years 5 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
CVPR
2008
IEEE
16 years 5 months ago
Automatic face naming with caption-based supervision
We consider two scenarios of naming people in databases of news photos with captions: (i) finding faces of a single person, and (ii) assigning names to all faces. We combine an in...
Matthieu Guillaumin, Thomas Mensink, Jakob J. Verb...
FGR
2006
IEEE
122views Biometrics» more  FGR 2006»
15 years 9 months ago
Head and Facial Action Tracking: Comparison of Two Robust Approaches
In this work, we address a method that is able to track simultaneously 3D head movements and facial actions like lip and eyebrow movements in a video sequence. In a baseline frame...
Romain Hérault, Franck Davoine, Yves Grandv...
115
Voted
AVSS
2006
IEEE
15 years 9 months ago
Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments
In this paper we report on techniques for automatically learning foveal sensing strategies for an active pan-tiltzoom camera. The approach uses reinforcement learning to discover ...
Andrew D. Bagdanov, Alberto Del Bimbo, Walter Nunz...
91
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Non-negative matrix deconvolution in noise robust speech recognition
High noise robustness has been achieved in speech recognition by using sparse exemplar-based methods with spectrogram windows spanning up to 300 ms. A downside is that a large exe...
Antti Hurmalainen, Jort F. Gemmeke, Tuomas Virtane...