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IROS
2009
IEEE
132views Robotics» more  IROS 2009»
14 years 2 months ago
Automatic selection of task spaces for imitation learning
Abstract— Previous work [1] shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imit...
Manuel Mühlig, Michael Gienger, Jochen J. Ste...
ICCV
2007
IEEE
14 years 9 months ago
What Can Casual Walkers Tell Us About A 3D Scene?
An approach for incremental learning of a 3D scene from a single static video camera is presented in this paper. In particular, we exploit the presence of casual people walking in...
Diego Rother, Kedar A. Patwardhan, Guillermo Sapir...
BMVC
2000
13 years 9 months ago
Quantifying Ambiguities in Inferring Vector-Based 3D Models
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
Eng-Jon Ong, Shaogang Gong
EMMCVPR
2001
Springer
14 years 3 days ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade
JAIR
2011
187views more  JAIR 2011»
13 years 2 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...