Marker-free kinematic skeleton estimation from sequences of volume data
Proceedings of the ACM symposium on Virtual reality software and technology
Automatic generation of personalized human avatars from multi-view video
Proceedings of the ACM symposium on Virtual reality software and technology
Example-based skeleton extraction
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Articulated mesh animation from multi-view silhouettes
ACM SIGGRAPH 2008 papers
Real-time and markerless 3D human motion capture using multiple views
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Robust spectral 3D-bodypart segmentation along time
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
A new approach for body pose recovery
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
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In computer animation, human motion capture from video is a widely used technique toacquire motion parameters. The acquisition process typically requires an intrusion into the scene in the form of optical markers which are used to estimate the parameters of motion as well as the kinematic structure of the performer. Marker-free optical motion captureapproaches exist, but due to their dependence on a specific type of a priori model they can hardly be used to track other subjects, e.g. animals. To bridge the gap between the generality of marker-based methods and the applicability of marker-free methods we present a flexible non-intrusive approach that estimates both, a kinematic model and its parameters of motion from a sequence of voxel-volumes. The volume sequences are reconstructed from multi-view video data by means of a shape-from-silhouette technique. The described method is well-suited for but not limited to motion capture of human subjects.