Handrix: animating the human hand
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Real-Time 3-D Hand Posture Estimation Based on 2-D Appearance Retrieval Using Monocular Camera
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Filtering Using a Tree-Based Estimator
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.