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» Factorial Learning and the EM Algorithm
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CVPR
2010
IEEE
14 years 3 months ago
Automatic Discovery of Meaningful Object Parts with Latent CRFs
Object recognition is challenging due to high intra-class variability caused, e.g., by articulation, viewpoint changes, and partial occlusion. Successful methods need to strike a...
Paul Schnitzspan, Stefan Roth, Bernt Schiele
PAMI
2008
179views more  PAMI 2008»
13 years 7 months ago
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
A dynamic texture is a spatio-temporal generative model for video, which represents video sequences as observations from a linear dynamical system. This work introduces the mixtur...
Antoni B. Chan, Nuno Vasconcelos
TIP
2008
157views more  TIP 2008»
13 years 7 months ago
Robust Face Tracking via Collaboration of Generic and Specific Models
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...
Peng Wang, Qiang Ji
JAIR
1998
198views more  JAIR 1998»
13 years 7 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
14 years 8 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda