  The problem of finding a next best viewpoint for 3D modeling or scene mapping
has been explored in computer vision over the last decade. This paper tackles a
similar problem, but with different characteristics. It proposes a method for
dynamic next best viewpoint recovery of a target point while avoiding possible
occlusions. Since the environment can change, the method has to iteratively
find the next best view with a global understanding of the free and occupied
parts.
  We model the problem as a set of possible viewpoints which correspond to the
centers of the facets of a virtual tessellated hemisphere covering the scene.
Taking into account occlusions, distances between current and future
viewpoints, quality of the viewpoint and joint constraints (robot arm joint
distances or limits), we evaluate the next best viewpoint. The proposal has
been evaluated on 8 different scenarios with different occlusions and a short
3D video sequence to validate its dynamic performance.
