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» A New Bayesian Framework for Object Recognition
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3DOR
2008
13 years 9 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
ICIP
2010
IEEE
13 years 5 months ago
Combining free energy score spaces with information theoretic kernels: Application to scene classification
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Manuele Bicego, Alessandro Perina, Vittorio Murino...
NIPS
2008
13 years 8 months ago
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
Daphna Weinshall, Hynek Hermansky, Alon Zweig, Jie...
CVPR
2012
IEEE
11 years 9 months ago
Robust visual tracking using autoregressive hidden Markov Model
Recent studies on visual tracking have shown significant improvement in accuracy by handling the appearance variations of the target object. Whereas most studies present schemes ...
Dong Woo Park, Junseok Kwon, Kyoung Mu Lee
IBPRIA
2005
Springer
14 years 17 days ago
A 3D Dynamic Model of Human Actions for Probabilistic Image Tracking
Abstract. In this paper we present a method suitable to be used for human tracking as a temporal prior in a particle filtering framework such as CONDENSATION [5]. This method is f...
Ignasi Rius, Daniel Rowe, Jordi Gonzàlez, F...