  We propose a new model-based method to accurately reconstruct human
performances captured outdoors in a multi-camera setup. Starting from a
template of the actor model, we introduce a new unified implicit representation
for both, articulated skeleton tracking and nonrigid surface shape refinement.
Our method fits the template to unsegmented video frames in two stages - first,
the coarse skeletal pose is estimated, and subsequently non-rigid surface shape
and body pose are jointly refined. Particularly for surface shape refinement we
propose a new combination of 3D Gaussians designed to align the projected model
with likely silhouette contours without explicit segmentation or edge
detection. We obtain reconstructions of much higher quality in outdoor settings
than existing methods, and show that we are on par with state-of-the-art
methods on indoor scenes for which they were designed

Computer Vision and Pattern Recognition