论文标题
使用神经形态摄像机进行对象分类的截止时间曲面
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras
论文作者
论文摘要
本文提出了一种新型的低级方法融合，以将维度降低为神经形态摄像机数据中的高级对象的有效方法，称为Inceptive事件时间曲面（IETS）。 IETS通过提高噪声的鲁棒性，促进空间一致性并改善（移动）边缘的时间定位来克服常规时间表面的几个局限性。将IET与转移学习结合起来可以改善利用事件摄像头数据的对象分类问题的最新性能。
This paper presents a novel fusion of low-level approaches for dimensionality reduction into an effective approach for high-level objects in neuromorphic camera data called Inceptive Event Time-Surfaces (IETS). IETSs overcome several limitations of conventional time-surfaces by increasing robustness to noise, promoting spatial consistency, and improving the temporal localization of (moving) edges. Combining IETS with transfer learning improves state-of-the-art performance on the challenging problem of object classification utilizing event camera data.
