  Motion deblurring is a critical ill-posed problem that is important in many
vision-based robotics applications. The recently proposed event-based double
integral (EDI) provides a theoretical framework for solving the deblurring
problem with the event camera and generating clear images at high frame-rate.
However, the original EDI is mainly designed for offline computation and does
not support real-time requirement in many robotics applications. In this paper,
we propose the fast EDI, an efficient implementation of EDI that can achieve
real-time online computation on single-core CPU devices, which is common for
physical robotic platforms used in practice. In experiments, our method can
handle event rates at as high as 13 million event per second in a wide variety
of challenging lighting conditions. We demonstrate the benefit on multiple
downstream real-time applications, including localization, visual tag
detection, and feature matching.
