OpenCV displaying a 2-channel image (optical flow) - image-processing

Question

I have optical flow stored in a 2-channel 32F matrix. I want to visualize the contents, what's the easiest way to do this?
How do I convert a CV_32FC2 to RGB with an empty blue channel, something imshow can handle? I am using OpenCV 2 C++ API.
Super Bonus Points
Ideally I would get the angle of flow in hue and the magnitude in brightness (with saturation at a constant 100%).

Answer 1

imshow can handle only 1-channel gray-scale and 3-4 channel BRG/BGRA images. So you need do a conversion yourself.
I think you can do something similar to:
//extraxt x and y channels
cv::Mat xy[2]; //X,Y
cv::split(flow, xy);
//calculate angle and magnitude
cv::Mat magnitude, angle;
cv::cartToPolar(xy[0], xy[1], magnitude, angle, true);
//translate magnitude to range [0;1]
double mag_max;
cv::minMaxLoc(magnitude, 0, &mag_max);
magnitude.convertTo(magnitude, -1, 1.0 / mag_max);
//build hsv image
cv::Mat _hsv[3], hsv;
_hsv[0] = angle;
_hsv[1] = cv::Mat::ones(angle.size(), CV_32F);
_hsv[2] = magnitude;
cv::merge(_hsv, 3, hsv);
//convert to BGR and show
cv::Mat bgr;//CV_32FC3 matrix
cv::cvtColor(hsv, bgr, cv::COLOR_HSV2BGR);
cv::imshow("optical flow", bgr);
cv::waitKey(0);

Answer 2

The MPI Sintel Dataset provides C and MatLab code for visualizing computed flow. Download the ground truth optical flow of the training set from here. The archive contains a folder flow_code containing the mentioned source code.
You can port the code to OpenCV, however, I wrote a simple OpenCV wrapper to easily use the provided code. Note that the method MotionToColor is taken from the color_flow.cpp file. Note the comments in the listing below.
// Important to include this before flowIO.h!
#include "imageLib.h"
#include "flowIO.h"
#include "colorcode.h"
// I moved the MotionToColor method in a separate header file.
#include "motiontocolor.h"
cv::Mat flow;
// Compute optical flow (e.g. using OpenCV); result should be
// 2-channel float matrix.
assert(flow.channels() == 2);
// assert(flow.type() == CV_32F);
int rows = flow.rows;
int cols = flow.cols;
CFloatImage cFlow(cols, rows, 2);
// Convert flow to CFLoatImage:
for (int i = 0; i < rows; i++) {
for (int j = 0; j < cols; j++) {
cFlow.Pixel(j, i, 0) = flow.at<cv::Vec2f>(i, j)[0];
cFlow.Pixel(j, i, 1) = flow.at<cv::Vec2f>(i, j)[1];
}
}
CByteImage cImage;
MotionToColor(cFlow, cImage, max);
cv::Mat image(rows, cols, CV_8UC3, cv::Scalar(0, 0, 0));
// Compute back to cv::Mat with 3 channels in BGR:
for (int i = 0; i < rows; i++) {
for (int j = 0; j < cols; j++) {
image.at<cv::Vec3b>(i, j)[0] = cImage.Pixel(j, i, 0);
image.at<cv::Vec3b>(i, j)[1] = cImage.Pixel(j, i, 1);
image.at<cv::Vec3b>(i, j)[2] = cImage.Pixel(j, i, 2);
}
}
// Display or output the image ...
Below is the result when using the Optical Flow code and example images provided by Ce Liu.