A System for Person-Independent Hand Posture Recognition against Complex Backgrounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Tracking of High DOF Articulated Structures: an Application to Human Hand Tracking
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Segment-Based Hand Pose Estimation
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Physically based grasping control from example
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Sign Recognition using Depth Image Streams
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Shape Classification Using the Inner-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hi-index | 0.00 |
The challenging problem of planning manipulation tasks for dexterous robotic hands can be significantly simplified if the robot system has the ability to learn manipulation skills by observing a human demonstrator. Toward this goal, we present a novel computer vision based hand posture recognition system to serve as an intelligent interface for skill transfer in robotic manipulation. We use the Inner Distance Shape Context (IDSC) as a hand shape descriptor to capture variations in the hand state (open or closed) under large in-plane rotations and considerable out-of-plane rotations. The proposed technique is further examined in applications involving grasp recognition and gesture based communications. The experiments show that the proposed approach can be generalized to recognizing a selected taxonomy of grasp types. At present, skin color is used to segment the hand region from the scene, but this method has its own limitations. We show preliminary results suggesting that the IDSC can be used to segment parts of the articulated object, including segmenting the hand from the human body silhouette without using skin color information.