Abstract
This paper proposes a framework for tracking both human hand kinematics and object contour during grasping task. The framework is based on modeling the object as point cloud and the use of marker-based tracking. We introduce how to estimate contact sites on both the hand and object, hand enclosing space, and graspable features from recorded data. Two experiments were performed to 1) verify the accuracy of contact site estimation (less than 5 mm), and 2) validate the feature extraction. Our approach can provide significant insight into how humans plan grasping and manipulation based on object recognition.
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