论文标题
基于事件的光流的距离表面
Distance Surface for Event-Based Optical Flow
论文作者
论文摘要
我们提出了Distsurf-of，这是一种用于神经形态摄像机的新型光流方法。神经形态摄像机（或事件检测摄像机）是一种新兴的传感器模态，它利用动态视觉传感器（DVS）来异步报告超过每个像素上预定义阈值的对数强度变化（称为“事件”）。在每个像素位置没有强度值的情况下，我们引入了“距离表面”的概念---从检测到的事件计算出的距离转换 - 作为对象纹理的代理。然后，距离表面用作基于强度的光流方法的输入，以恢复二维像素运动。实际传感器实验验证了所提出的脉冲脉冲准确估计每个事件的角度和速度。
We propose DistSurf-OF, a novel optical flow method for neuromorphic cameras. Neuromorphic cameras (or event detection cameras) are an emerging sensor modality that makes use of dynamic vision sensors (DVS) to report asynchronously the log-intensity changes (called "events") exceeding a predefined threshold at each pixel. In absence of the intensity value at each pixel location, we introduce a notion of "distance surface"---the distance transform computed from the detected events---as a proxy for object texture. The distance surface is then used as an input to the intensity-based optical flow methods to recover the two dimensional pixel motion. Real sensor experiments verify that the proposed DistSurf-OF accurately estimates the angle and speed of each events.
