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CVPR
2009
IEEE
17 years 1 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
CVPR
2001
IEEE
16 years 8 months ago
Semi-Dense Stereo Correspondence with Dense Features
We present a new feature based algorithm for stereo correspondence. Most of the previous feature based methods match sparse features like edge pixels, producing only sparse dispar...
Olga Veksler
CVPR
2006
IEEE
16 years 8 months ago
Perception Strategies in Hierarchical Vision Systems
Flat appearance-based systems, which combine clever image representations with standard classifiers, might be the most effective way to recognize objects using current technologie...
Lior Wolf, Stanley M. Bileschi, Ethan Meyers
ICPR
2006
IEEE
16 years 7 months ago
Adaptive Feature Integration for Segmentation of 3D Data by Unsupervised Density Estimation
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
Marco Cristani, Umberto Castellani, Vittorio Murin...
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 7 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher