  Event cameras are promising devices for lowlatency tracking and high-dynamic
range imaging. In this paper,we propose a novel approach for 6
degree-of-freedom (6-DoF)object motion tracking that combines measurements of
eventand frame-based cameras. We formulate tracking from highrate events with a
probabilistic generative model of the eventmeasurement process of the object.
On a second layer, we refinethe object trajectory in slower rate image frames
through directimage alignment. We evaluate the accuracy of our approach
inseveral object tracking scenarios with synthetic data, and alsoperform
experiments with real data.
