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ATAL
2008
Springer
14 years 11 months ago
Learning to interact: connecting perception with action in virtual environments
Modeling synthetic characters which interact with objects in dynamic virtual worlds is important when we want the agents to act in an autonomous and non-preplanned way. Such inter...
Pedro Sequeira, Ana Paiva
AAAI
1994
14 years 11 months ago
High Dimension Action Spaces in Robot Skill Learning
Table lookup with interpolation is used for many learning and adaptation tasks. Redundant mappings capture the important concept of \motor skill," which is important in real,...
Jeff G. Schneider
NIPS
2008
14 years 11 months ago
Learning a discriminative hidden part model for human action recognition
We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden conditi...
Yang Wang 0003, Greg Mori
CIARP
2009
Springer
15 years 4 months ago
Learning Relational Grammars from Sequences of Actions
Many tasks can be described by sequences of actions that normally exhibit some form of structure and that can be represented by a grammar. This paper introduces FOSeq, an algorithm...
Blanca Vargas-Govea, Eduardo F. Morales
CVPR
2008
IEEE
15 years 11 months ago
Learning human actions via information maximization
In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a ba...
Jingen Liu, Mubarak Shah