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» Learning Multiple Latent Variables with Self-Organizing Maps
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CRV
2008
IEEE
295views Robotics» more  CRV 2008»
14 years 3 months ago
3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
Kooksang Moon, Vladimir Pavlovic
IJIS
2008
123views more  IJIS 2008»
13 years 9 months ago
Algorithms of nonlinear document clustering based on fuzzy multiset model
Abstract: Fuzzy multiset is applicable as a model of information retrieval because it has the mathematical structure which expresses the number and the degree of attribution of an ...
Kiyotaka Mizutani, Ryo Inokuchi, Sadaaki Miyamoto
ICML
2010
IEEE
13 years 10 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
CVPR
2012
IEEE
11 years 11 months ago
Top-down visual saliency via joint CRF and dictionary learning
Top-down visual saliency facilities object localization by providing a discriminative representation of target objects and a probability map for reducing the search space. In this...
Jimei Yang, Ming-Hsuan Yang
ICASSP
2009
IEEE
14 years 3 months ago
Multi-view tracking of articulated human motion in silhouette and pose manifolds
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...
Feng Guo, Gang Qian