Fast and accurate auto-focus in adverse conditions remains an arduous task. The emergence of event cameras has opened up new possibilities for addressing the challenge. This paper presents a new high-speed and accurate event-based focusing algorithm. 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 event-based autofocus dataset (EAD) 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且准确的自动对焦仍是一项艰巨任务。事件相机的出现为解决这一挑战开辟了新的可能性。本文提出了一种基于事件的高速精确对焦算法。具体而言，研究了对焦过程中事件极性的对称关系，并根据事件相机原理及对焦过程中的成像模型提出了基于事件的焦点评价函数。在公开的事件相机自动对焦数据集（EAD）上的综合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，在0.004秒内实现了小于一个焦深的精确对焦。数据集和代码将公开发布。