Authors:
Rui Liu
;
Burkhard C. Wünsche
;
Christof Lutteroth
and
Patrice Delmas
Affiliation:
University of Auckland, New Zealand
Keyword(s):
Hand tracking, Hand segmentation, Skin classifiers, Hand rehabilitation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Human-Computer Interaction
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Semantic Representation of Motion and Animation
Abstract:
Applications for home-based care are rapidly increasing in importance due to spiraling health and elderly care costs. An important aspect of home-based care is exercises for rehabilitation and improving general health. In this paper we present a framework for demonstrating and monitoring hand exercises. The three main components are a 3D hand model, a high-level animation framework which facilitates the task of specifying hand exercises via skeletal animation, and a hand tracking program to monitor and evaluate users’ performance.
Our hand tracking solution has no calibration stage and is easily set-up. Segmentation is performed using a perception-based colour space, and hand tracking and motion estimate are obtained using novel variations to a CAMSHIFT and contour analysis algorithms. The results indicate that the robust tracking along with the demonstration and reconstruction of hand exercises provide an effective platform for hand rehabilitation.