A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework
Channel: Event-based Robot Vision
Date: 2022-12-17

Project page: https://github.com/tub-rip/event_collapse
PDF: https://arxiv.org/pdf/2212.07350
Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-of-the-art accuracy on motion estimation using events, may suffer from an overfitting problem called event collapse. Prior works are computationally expensive or cannot alleviate the overfitting, which undermines the benefits of the CMax framework. We propose a novel, computationally efficient regularizer based on geometric principles to mitigate event collapse. The experiments show that the proposed regularizer achieves state-of-the-art accuracy results, while its reduced computational complexity makes it two to four times faster than previous approaches. To the best of our knowledge, our regularizer is the only effective solution for event collapse without trading off runtime. We hope our work opens the door for future applications that unlocks the advantages of event cameras.

Reference:
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework,
Advanced Intelligent Systems 2022, 2022.

Event-based Vision:
- Event Collapse in Contrast Maximization Frameworks: https://arxiv.org/abs/2207.04007
- Secrets of Event-Based Optical Flow (ECCV 2022) https://github.com/tub-rip/event_based_optical_flow
- Research: https://sites.google.com/view/guillermogallego/research/event-based-vision
- Survey paper: https://arxiv.org/abs/1904.08405
- Course at TU Berlin: https://sites.google.com/view/guillermogallego/teaching/event-based-robot-vision

Affiliation:
Shintaro Shiba and Yoshimitsu Aoki are with the Faculty of Science and Technology, Keio University, Kanagawa, Japan.
Guillermo Gallego is with TU Berlin, the Einstein Center Digital Future and the SCIoI Excellence Cluster, Berlin, Germany.