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» Learning Articulated Structure and Motion
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RAS
2010
109views more  RAS 2010»
13 years 6 months ago
Combining active learning and reactive control for robot grasping
Grasping an object is a task that inherently needs to be treated in a hybrid fashion. The system must decide both where and how to grasp the object. While selecting where to grasp...
Oliver Krömer, Renaud Detry, Justus H. Piater...
ICPR
2000
IEEE
14 years 8 months ago
Estimation of the Location of Joint Points of Human Body from Successive Volume Data
Recognizing structure of human body is important for modeling human motion. Human body is usually represented as an articulate model, which consists of the rigid parts and the joi...
Masaaki Iiyama, Yoshinari Kameda, Michihiko Minoh
ECCV
2008
Springer
13 years 9 months ago
Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
Junbiao Pang, Qingming Huang, Shuqiang Jiang
CVPR
2010
IEEE
14 years 4 months ago
Modeling Mutual Context of Object and Human Pose in Human-Object Interaction Activities
Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in ac...
Bangpeng Yao, Li Fei-Fei
ICML
1994
IEEE
13 years 11 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager