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NIPS
1998
13 years 12 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
NIPS
1997
13 years 12 months ago
Active Data Clustering
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...
Thomas Hofmann, Joachim M. Buhmann
NIPS
1997
13 years 12 months ago
Graph Matching with Hierarchical Discrete Relaxation
Our aim in this paper is to develop a Bayesian framework for matching hierarchical relational models. Such models are widespread in computer vision. The framework that we adopt fo...
Richard C. Wilson, Edwin R. Hancock
DAGM
2009
Springer
13 years 11 months ago
Depth Imaging by Combining Time-of-Flight and On-Demand Stereo
In this paper we present a framework for computing depth images at interactive rates. Our approach is based on combining time-of-flight (TOF) range data with stereo vision. We use ...
Uwe Hahne, Marc Alexa

Publication
313views
13 years 11 months ago
Visual Surveillance: Dynamic Behavior Analysis at Multiple Levels
New cameras are installed daily all around the world. Hence it becomes increasingly important to develop methods for reducing the manual effort that is still required for video ana...
Michael D. Breitenstein