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CPAIOR
2009
Springer
16 years 1 months ago
Learning How to Propagate Using Random Probing
Abstract. In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usu...
Efstathios Stamatatos, Kostas Stergiou
IROS
2007
IEEE
171views Robotics» more  IROS 2007»
16 years 1 months ago
Learning full-body motions from monocular vision: dynamic imitation in a humanoid robot
— In an effort to ease the burden of programming motor commands for humanoid robots, a computer vision technique is developed for converting a monocular video sequence of human p...
Jeffrey B. Cole, David B. Grimes, Rajesh P. N. Rao
MM
2005
ACM
112views Multimedia» more  MM 2005»
16 years 9 days ago
MediaMill: exploring news video archives based on learned semantics
In this technical demonstration we showcase the MediaMill system. A search engine that facilitates access to news video archives at a semantic level. The core of the system is an ...
Cees Snoek, Marcel Worring, Jan van Gemert, Jan-Ma...
EMMCVPR
2005
Springer
16 years 8 days ago
Learning Hierarchical Shape Models from Examples
Abstract. We present an algorithm for automatically constructing a decompositional shape model from examples. Unlike current approaches to structural model acquisition, in which on...
Alex Levinshtein, Cristian Sminchisescu, Sven J. D...
ECAI
2004
Springer
16 years 4 days ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana