Fast and accurate auto-focus in adverse conditions remains an arduous task. The paper presents a polarity-based event camera auto-focus algorithm featuring high-speed, precise auto-focus in dark, dynamic scenes that conventional frame-based cameras cannot match. Specifically, the symmetrical relationship between the event polarities in focusing is investigated, and the event-based focus evaluation function is proposed based on the principles of the event cameras and the imaging model in the focusing process. Comprehensive experiments on the public EAD dataset show the robustness of the model. Furthermore, precise focus with less than one depth of focus is achieved within 0.004 seconds on our self-built high-speed focusing platform. The dataset and code will be made publicly available.

翻译：在恶劣条件下实现快速准确的自动对焦仍然是一项艰巨任务。本文提出了一种基于极性的事件相机自动对焦算法，能够在传统帧相机无法匹敌的黑暗、动态场景中实现高速、精确的自动对焦。具体而言，研究了对焦过程中事件极性之间的对称关系，并基于事件相机的原理及对焦过程中的成像模型，提出了基于事件的焦点评估函数。在公开的EAD数据集上进行的全面实验证明了该模型的鲁棒性。此外，在我们自建的高速对焦平台上，能在0.004秒内实现小于一个焦深的精确对焦。数据集和代码将公开提供。