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Markerless motion capture of interacting characters using multi-view image segmentation

Y. Liu and C. Stoll and J. Gall and H.-P. Seidel and C. Theobalt
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
2011

Abstract

We present a markerless motion capture approach that reconstructs the skeletal motion and detailed time-varying surface geometry of two closely interacting people from multi-view video. Due to ambiguities in feature-to-person assignments and frequent occlusions, it is not feasible to directly apply single-person capture approaches to the multiperson case. We therefore propose a combined image segmentation and tracking approach to overcome these difficulties. A new probabilistic shape and appearance model is employed to segment the input images and to assign each pixel uniquely to one person. Thereafter, a single-person markerless motion and surface capture approach can be applied to each individual, either one-by-one or in parallel, even under strong occlusions. We demonstrate the performance of our approach on several challenging multi-person motions, including dance and martial arts, and also provide a reference dataset for multi-person motion capture with ground truth.


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@InProceedings{eth_biwi_00859,
  author = {Y. Liu and C. Stoll and J. Gall and H.-P. Seidel and C. Theobalt},
  title = {Markerless motion capture of interacting characters using multi-view image segmentation},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2011},
  pages = {1249-1256},
  keywords = {}
}