Real-Time Panoramic Tracking for Event Cameras
This work addresses camera tracking for event cameras, which is important for robotics and AR/VR applications, but it appears incremental as it adapts existing visual odometry methods to a new sensor modality.
The paper tackles real-time camera tracking for event cameras in a panoramic setting with three degrees of freedom, proposing a direct method that uses only spatial event positions without scene appearance, and demonstrates robustness to fast movements and dynamic objects on existing and new datasets.
Event cameras are a paradigm shift in camera technology. Instead of full frames, the sensor captures a sparse set of events caused by intensity changes. Since only the changes are transferred, those cameras are able to capture quick movements of objects in the scene or of the camera itself. In this work we propose a novel method to perform camera tracking of event cameras in a panoramic setting with three degrees of freedom. We propose a direct camera tracking formulation, similar to state-of-the-art in visual odometry. We show that the minimal information needed for simultaneous tracking and mapping is the spatial position of events, without using the appearance of the imaged scene point. We verify the robustness to fast camera movements and dynamic objects in the scene on a recently proposed dataset and self-recorded sequences.