SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Predicting Missing Markers to Drive Real-Time Centre of Rotation Estimation
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
A hybrid approach towards fully automatic 3D marker tracking
Proceedings of the 2008 ACM symposium on Virtual reality software and technology
Intelligent Motion Tracking by Combining Specialized Algorithms
ICDHM '09 Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009
Real-time automatic kinematic model building for optical motion capture using a Markov random field
HCI'07 Proceedings of the 2007 IEEE international conference on Human-computer interaction
Efficient marker matching using pair-wise constraints in physical therapy
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Full body interaction for serious games in motor rehabilitation
Proceedings of the 2nd Augmented Human International Conference
Bilinear spatiotemporal basis models
ACM Transactions on Graphics (TOG)
Predicting missing markers in real-time optical motion capture
3DPH'09 Proceedings of the 2009 international conference on Modelling the Physiological Human
Optical tracking and calibration of tangible interaction devices
EGVE'05 Proceedings of the 11th Eurographics conference on Virtual Environments
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Building intuitive user-interfaces for Virtual Reality applications is a difficult task, as one of the main purposes is to provide a "natural", yet efficient input device to interact with the virtual environment. One particularly interesting approach is to track and retarget the complete motion of a subject. Established techniques for full body motion capture like optical motion tracking exist. However, due to their computational complexity and their reliance on pre-specified models, they fail to meet the demanding requirements of Virtual Reality environments such as real-time response, immersion, and ad hoc configurability. Our goal is to support the use of motion capture as a general input device for Virtual Reality applications. In this paper we present a self-calibrating framework for optical motion capture, enabling the reconstruction and tracking of arbitrary articulated objects in real-time. Our method automatically estimates all relevant model parameters on-the-fly without any information on the initial tracking setup or the marker distribution, and computes the geometry and topology of multiple tracked skeletons. Moreover, we show how the model can make the motion capture phase robust against marker occlusions by exploiting the redundancy in the skeleton model and by reconstructing missing inner limbs and joints of the subject from partial information. Meeting the above requirements our system is well applicable to a wide range of Virtual Reality based applications, where unconstrained tracking and flexible retargeting of motion data is desirable.