This survey reviews advances in human motion capture and analysis from 2000 to 2006,
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …

Human motion tracking for rehabilitation has been an active research topic since the 1980s.
It has been motivated by the increased number of patients who have suffered a stroke, or …

Due to the lack of camera parameter information for in-the-wild images, existing 3D human
pose and shape (HPS) estimation methods make several simplifying assumptions: weak …

Markerless vision-based human motion analysis has the potential to provide an
inexpensive, non-obtrusive solution for the estimation of body poses. The significant …

In this work we present an approach for markerless motion capture (MoCap) of articulated
objects, which are recorded with multiple unsynchronized moving cameras. Instead of using …

In Part I of this paper we developed the theory and algorithms for performing Shape-From-
Silhouette (SFS) across time. In this second part, we show how our temporal SFS algorithms …

In the era of deep learning, human pose estimation from multiple cameras with unknown
calibration has received little attention to date. We show how to train a neural model to …

Capturing human motion in natural scenarios means moving motion capture out of the lab
and into the wild. Typical approaches rely on fixed, calibrated, cameras and reflective …

Research into tracking and recognizing human movement has so far been mostly limited to
gait or frontal posing. Part I of this paper presents a continuous human movement …

Reconstructing 3D human poses from a single 2D image is an ill-posed problem without
considering the human body model. Explicitly enforcing physiological constraints is known …