Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization

This paper addresses the problem of rotational motion estimation using event cameras. Several event-based rotation estimation methods have been developed in the past decade, without considering a global refinement step. To this end, we propose the first event-based rotation-only bundle adjustment (BA) approach. We formulate it leveraging the state-of-the-art Contrast Maximization (CMax) framework, which is principled and avoids the need to convert events into frames. In addition, we use the proposed BA to build CMax-SLAM, the first event-based rotation-only SLAM system comprising a front-end and a back-end. Our BA is able to run both offline (trajectory smoothing) and online (CMax-SLAM back-end). We demonstrate the proposed method in a variety of scenarios, which shows state-of-the-art performance. Project page and full paper: https://github.com/tub-rip/cmax_slam