用自适应时间表面和极性感知提升事件相机的单目惯性定位精度
Monocular Event-Inertial Odometry with Adaptive decay-based Time Surface and Polarity-aware Tracking
- 用自适应衰减核构建时间表面，更好捕捉动态事件纹理
- 引入反极性时间表面，有效缓解运动方向变化时的特征漂移
- 在多个数据集上超越现有方法，适合高动态场景定位
事件相机因其低功耗、高动态范围和无运动模糊等优势受到广泛关注。本文提出一种基于自适应衰减核时间表面与极性感知追踪的单目事件-惯性里程计方法。通过自适应衰减机制提取异步事件中的纹理信息，能够随事件流动态特性调整，增强环境纹理表征能力。然而，极性加权时间表面在运动方向改变时易受极性翻转影响，导致特征追踪退化。为此，本文引入额外的极性反转时间表面，显著提升追踪鲁棒性。与视觉-惯性及事件-惯性里程计方法的对比分析表明，所提方法在多个数据集上均优于现有先进水平，表现出优异的定位性能。
原文摘要 · Abstract (English)
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.
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