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127
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WACV
2005
IEEE
15 years 8 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
109
Voted
ICMCS
2006
IEEE
112views Multimedia» more  ICMCS 2006»
15 years 8 months ago
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
The Feature Vector approach is one of the most popular schemes for managing multimedia data. For many data types such as audio, images, or 3D models, an abundance of different Fea...
Tobias Schreck, Daniel A. Keim, Christian Panse
NIPS
2001
15 years 4 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
147
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AIPR
2002
IEEE
15 years 7 months ago
ICA Mixture Model based Unsupervised Classification of Hyperspectral Imagery
Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
Chintan A. Shah, Manoj K. Arora, Stefan A. Robila,...
EMMCVPR
1997
Springer
15 years 6 months ago
Deterministic Annealing for Unsupervised Texture Segmentation
Abstract. In this paper a rigorous mathematical framework of deterministic annealing and mean-field approximation is presented for a general class of partitioning, clustering and ...
Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann