Model-based Outdoor Performance Capture
This addresses the challenge of accurate outdoor human performance capture for applications like animation or virtual reality, representing an incremental improvement by adapting methods to outdoor conditions.
The paper tackles the problem of reconstructing human performances outdoors using a multi-camera setup, achieving higher quality reconstructions in outdoor settings compared to existing methods and matching state-of-the-art performance on indoor scenes.
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