Tracking 6-DoF Object Motion from Events and Frames

Haolong Li, Joerg Stueckler

Abstract: Event cameras are promising devices for low latency 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 event and frame-based cameras. We formulate tracking from high rate events with a probabilistic generative model of the event measurement process of the object. On a second layer, we refine the object trajectory in slower rate image frames through direct image alignment. We evaluate the accuracy of our approach in several object tracking scenarios with synthetic data, and also perform experiments with real data.