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» A Hierarchical Latent Variable Model for Data Visualization
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SSPR
2004
Springer
14 years 2 months ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli
ICML
2000
IEEE
14 years 9 months ago
Hierarchical Unsupervised Learning
We consider the problem of unsupervised classification of temporal sequences of facial expressions in video. This problem arises in the design of an adaptive visual agent, which m...
Shivakumar Vaithyanathan, Byron Dom
CVPR
2007
IEEE
14 years 10 months ago
Semi-supervised Hierarchical Models for 3D Human Pose Reconstruction
Recent research in visual inference from monocular images has shown that discriminatively trained image-based predictors can provide fast, automatic qualitative 3D reconstructions...
Atul Kanaujia, Cristian Sminchisescu, Dimitris N. ...
FTCGV
2011
122views more  FTCGV 2011»
13 years 8 days ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
PAMI
2006
136views more  PAMI 2006»
13 years 8 months ago
Data Driven Image Models through Continuous Joint Alignment
This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar a...
Erik G. Learned-Miller