Automatic acquisition and initialization of articulated models
Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
Integration of Vision and Inertial Sensors for 3D Arm Motion Tracking in Home-based Rehabilitation
International Journal of Robotics Research
Multicamera tracking of articulated human motion using shape and motion cues
IEEE Transactions on Image Processing
Human motion modeling using multivision
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Multi-camera tracking of articulated human motion using motion and shape cues
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Forward non-rigid motion tracking for facial MoCap
The Visual Computer: International Journal of Computer Graphics
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Human motion capture has lately been the object of much attention due to commercial interests. A "touch free" computer vision solution to the problem is desirable to avoid the intrusiveness of standard capture devices. The object to be monitored is known a priori which suggest to include a human model in the capture process. In this paper we use a model-based approach known as the analysis-by-synthesis approach. This approach is powerful but has a problem with its potential huge search space. Using multiple cues we reduce the search space by introducing constraints through the 3D locations of salient points and a silhouette of the subject. Both data types are relatively easy to derive and only require limited computational effort so the approach remains suitable for real-time applications. The approach is tested on 3D movements of a human arm and the results show that we successfully can estimate the pose of the arm using the reduced search space.