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BMVC
2010
15 years 1 months ago
Back to the Future: Learning Shape Models from 3D CAD Data
Recognizing 3D objects from arbitrary view points is one of the most fundamental problems in computer vision. A major challenge lies in the transition between the 3D geometry of o...
Michael Stark, Michael Goesele, Bernt Schiele
155
Voted
ECAI
2010
Springer
15 years 29 days ago
Adaptive Markov Logic Networks: Learning Statistical Relational Models with Dynamic Parameters
Abstract. Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects...
Dominik Jain, Andreas Barthels, Michael Beetz
ICPR
2004
IEEE
16 years 4 months ago
Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Miha Peternel, Ales Leonardis
137
Voted
GPEM
2002
104views more  GPEM 2002»
15 years 3 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
152
Voted
ICMCS
2009
IEEE
103views Multimedia» more  ICMCS 2009»
15 years 1 months ago
Web image retrieval via learning semantics of query image
The performance of traditional image retrieval approaches remains unsatisfactory, as they are restricted by the wellknown semantic gap and the diversity of textual semantics. To t...
Chuanghua Gui, Jing Liu, Changsheng Xu, Hanqing Lu