  Egocentric 3D human pose estimation using a single fisheye camera has become
popular recently as it allows capturing a wide range of daily activities in
unconstrained environments, which is difficult for traditional outside-in
motion capture with external cameras. However, existing methods have several
limitations. A prominent problem is that the estimated poses lie in the local
coordinate system of the fisheye camera, rather than in the world coordinate
system, which is restrictive for many applications. Furthermore, these methods
suffer from limited accuracy and temporal instability due to ambiguities caused
by the monocular setup and the severe occlusion in a strongly distorted
egocentric perspective. To tackle these limitations, we present a new method
for egocentric global 3D body pose estimation using a single head-mounted
fisheye camera. To achieve accurate and temporally stable global poses, a
spatio-temporal optimization is performed over a sequence of frames by
minimizing heatmap reprojection errors and enforcing local and global body
motion priors learned from a mocap dataset. Experimental results show that our
approach outperforms state-of-the-art methods both quantitatively and
qualitatively.
