Tracking 6-DoF Object Motion from Events and Frames
This addresses low-latency, high-dynamic range tracking for robotics or vision applications, but appears incremental as it builds on existing event and frame fusion methods.
The paper tackles the problem of 6-DoF object motion tracking by combining event and frame-based cameras, achieving accurate tracking in synthetic and real data scenarios.
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.