本文介绍了如何利用已知的深度和相机位姿信息在视频帧之间进行简单的光流计算。通过计算每个像素的运动，无需复杂算法即可确定像素的运动方向和大小。使用HSV颜色空间表示光流，H通道表示像素方向，V通道表示运动幅度。在Unreal Engine和AirSim模拟的无人机场景中，展示了这种光流计算方法，以及如何将结果导入MeshLab检查深度和相机位姿的一致性，并进行了图像扭曲以从第二个帧的视角查看第一个帧。
实在时间紧，还是仅上英文版的，诸位见谅。原文在我的个人主页上。
Simple optical flow based on depth and pose information
Recently, I was helping to implement a simple program that performs optical flow calculation between frames of video images with the help of known depth and pose information associated with the images.
Let us define the first frame as Frame 0, and the second to be Frame 1. And for my current task, the camera is under constant movement. For optical flow, it is usually represented by a color image with HSV color space. In this image, Channel H (Hue) is used to represent the flow direction of the individual pixel of the Frame 0. That is if the camera is moving, every pixel of Frame 0 seems to move with respect to Frame 1 and exhibiting a representative color regarding the flow direction. Channel V (Value or Lightness) tells the magnitude of the movement of a pixel. The larger the movement, the brighter it should be. We leave the S (Saturation) Channel to be its highest value and never touch it.
The thing is, once you know the camera pose and depth information of each frame, you know everything. No fancy algorithm is needed to perform optical flow calculation since you can calculate the movement of the individual pixel. The overall process looks very much like the following.
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