Monocular Event-Inertial Odometry with Adaptive decay-based Time Surface and Polarity-aware Tracking

TL;DR

This paper introduces a monocular event-inertial odometry method that uses an adaptive decay-based time surface and polarity-aware tracking to improve environmental texture representation and robustness against motion polarity shifts.

Contribution

It proposes a novel adaptive decay kernel-based time surface and a polarity-inverted time surface for enhanced feature tracking in event-inertial odometry.

Findings

Outperforms state-of-the-art methods on various datasets.

Enhances texture representation with adaptive decay time surface.

Improves robustness to motion polarity changes.

Abstract

Event cameras have garnered considerable attention due to their advantages over traditional cameras in low power consumption, high dynamic range, and no motion blur. This paper proposes a monocular event-inertial odometry incorporating an adaptive decay kernel-based time surface with polarity-aware tracking. We utilize an adaptive decay-based Time Surface to extract texture information from asynchronous events, which adapts to the dynamic characteristics of the event stream and enhances the representation of environmental textures. However, polarity-weighted time surfaces suffer from event polarity shifts during changes in motion direction. To mitigate its adverse effects on feature tracking, we optimize the feature tracking by incorporating an additional polarity-inverted time surface to enhance the robustness. Comparative analysis with visual-inertial and event-inertial odometry methods shows that our approach outperforms state-of-the-art techniques, with competitive results across various datasets.