论文标题
基于事件的成像赛车测定 - 基于事件的摄像机的评估用于测量流体流量
Event-based Imaging Velocimetry -- An Assessment of Event-based Cameras for the Measurement of Fluid Flows
论文作者
论文摘要
与传统的基于帧的成像，基于事件的视觉（EBV）或动态视觉传感（DVS）异步记录具有微秒分辨率给定像素的强度变化的二元信号。目前的工作探讨了利用基于事件的流体流量测量的愿景的潜力的可能性。所描述的基于事件的成像速度计（EBIV）的实现依赖于被激光光片照亮的小颗粒，该颗粒类似于经典的二维，两种组件（2D-2C）PIV，其差异是不连续操作的激光板不使用激光器或相机的调节。移动粒子在检测器上产生连续的时型事件，后来使用斑块处理方案来推断其速度。提出了两种流量估计算法；一种使用“运动补偿”最大化局部对比度，另一个是基于相关方法的。基础运动检测方案以及完全没有背景信号的情况，可以直接检索与单个颗粒相关的事件，从而允许重建单个粒子轨道。另外，可以使用从事件数据流重建的图像使用常规PIV算法处理事件数据。这些概念在水和空气中的简单流程上得到了证明。
Contrary to conventional frame-based imaging, event-based vision (EBV) or dynamic vision sensing (DVS) asynchronously records binary signals of intensity changes for given pixels with microsecond resolution. The present work explores the possibilities of harnessing the potentials of event-based vision for fluid flow measurement. The described implementations of event-based imaging velocimetry (EBIV) rely on the imaging small particles that are illuminated by a laser light sheet which is similar to classical two-dimensional, two-component (2d-2c) PIV with the difference that a continuously operating laser-light sheet is used without modulation of the laser or camera. The moving particles generate continuous time-stamped events on the detector that are later used to infer their velocity using patch-wise processing schemes. Two flow estimation algorithms are proposed; one uses a "motion compensation" that maximizes the local contrast, the other is based on a sum-of-correlations approach. The underlying motion detection schemes along with the complete absence of background signal allows straightforward retrieval of the events associated with individual particles thereby allowing the reconstruction of individual particle tracks. Alternatively, the event data can be processed with conventional PIV algorithms using images reconstructed from the event data stream. The concepts are demonstrated on simple flows in water and air.
