  This letter presents a novel approach to extract reliable dense and
long-range motion trajectories of articulated human in a video sequence.
Compared with existing approaches that emphasize temporal consistency of each
tracked point, we also consider the spatial structure of tracked points on the
articulated human. We treat points as a set of vertices, and build a triangle
mesh to join them in image space. The problem of extracting long-range motion
trajectories is changed to the issue of consistency of mesh evolution over
time. First, self-occlusion is detected by a novel mesh-based method and an
adaptive motion estimation method is proposed to initialize mesh between
successive frames. Furthermore, we propose an iterative algorithm to
efficiently adjust vertices of mesh for a physically plausible deformation,
which can meet the local rigidity of mesh and silhouette constraints. Finally,
we compare the proposed method with the state-of-the-art methods on a set of
challenging sequences. Evaluations demonstrate that our method achieves
favorable performance in terms of both accuracy and integrity of extracted
trajectories.
