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CPAIOR
2009
Springer
15 years 11 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»
15 years 10 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»
15 years 10 months 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
15 years 10 months 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
15 years 10 months 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