Performance capture of interacting characters with handheld kinects
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Real-time human pose tracking from range data
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Full body performance capture under uncontrolled and varying illumination: a shading-based approach
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Content-aware exaggerated editing for life-like captured animations
Proceedings of the 9th European Conference on Visual Media Production
HandSonor: a customizable vision-based control interface for musical expression
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Alternative performance capturing
ACM SIGGRAPH 2013 Studio Talks
On-set performance capture of multiple actors with a stereo camera
ACM Transactions on Graphics (TOG)
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We present an approach for modeling the human body by Sums of spatial Gaussians (SoG), allowing us to perform fast and high-quality markerless motion capture from multi-view video sequences. The SoG model is equipped with a color model to represent the shape and appearance of the human and can be reconstructed from a sparse set of images. Similar to the human body, we also represent the image domain as SoG that models color consistent image blobs. Based on the SoG models of the image and the human body, we introduce a novel continuous and differentiable model-to-image similarity measure that can be used to estimate the skeletal motion of a human at 5 -- 15 frames per second even for many camera views. In our experiments, we show that our method, which does not rely on silhouettes or training data, offers an good balance between accuracy and computational cost.