PoseRBPF: A new particle filter for 6D object pose tracking

Researchers at NVIDIA, University of Washington, Stanford University, and University of Illinois Urbana-Champaign have recently developed a Rao-Blackwellized particle filter for 6-D pose tracking, called PoseRBPF. The approach can effectively estimate the 3-D translation of an object and its full distribution over the 3-D rotation. The paper describing this filter, pre-published on arXiv, will be presented at the upcoming Robotics Science and Systems Conference in Freiburg, Germany.

* This article was originally published here