Frame-based optical flow (OF) methods struggle in the presence of large motion and occlusion due to slow frame rates. Optical flow of dynamic vision sensor (DVS) has gained attention recently as a way to overcome these shortcomings. DVS reports “events” corresponding log intensity changes exceeding a specific threshold, with an accuracy of microsecond order. The increased temporal sampling rate are indeed helpful, but the poor spatial fidelity of DVS outputs make events-based OF less reliable overall. In this work, we consider a new sensor called DAViS that combines the conventional active pixel sensor (APS) and DVS circuitries, yielding a conventional intensity image frames as well as the events. We propose a novel optical flow method designed specifically for a DAViS camera that leverages the high spatial fidelity of intensity image frames and the high temporal resolution of events generated by DVS. Hence, the proposed DAViS-OF method yields reliable motion vector estimates while overcoming the fast motion and occlusion problems. The proposed DAViS-OF method is computationally efficient and is suitable for real-time implementation.

中文翻译：

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DAViS 相机光流

由于帧速率较慢，基于帧的光流 (OF) 方法在存在大运动和遮挡的情况下会遇到困难。动态视觉传感器（DVS）的光流最近作为克服这些缺点的一种方式而受到关注。DVS 报告“事件”对应的日志强度变化超过特定阈值，精度为微秒级。增加的时间采样率确实有帮助，但 DVS 输出的空间保真度较差，使得基于事件的 OF 总体上不太可靠。在这项工作中，我们考虑了一种称为 DAViS 的新传感器，它结合了传统的有源像素传感器 (APS) 和 DVS 电路，产生了传统强度的图像帧和事件。我们提出了一种专为 DAViS 相机设计的新型光流方法，该方法利用了强度图像帧的高空间保真度和 DVS 生成的事件的高时间分辨率。因此，所提出的 DAViS-OF 方法在克服快速运动和遮挡问题的同时产生可靠的运动矢量估计。提出的 DAViS-OF 方法计算效率高，适合实时实现。