OpenCV Optical Flow assertion
I'm attempting to track landmarks along the contour of facial features obtained via dsift with python 2.7 and openCV 2.4.11. I want to track these features between frames.
However I am receiving the following error. I have checked the input images are 1-channel equal dimensions (and unsigned 8bit type), and likewise with the prev points:
OpenCV Error: Assertion failed ((npoints = prevPtsMat.checkVector(2, CV_32F, tru
e)) >= 0) in cv::calcOpticalFlowPyrLK, file ..\..\..\modules\video\src\lkpyramid.cpp
cv2.error: ..\..\..\modules\video\src\lkpyramid.cpp:845: error: (-215) (npoints
= prevPtsMat.checkVector(2, CV_32F, true)) >= 0 in function cv::calcOpticalFlowP
yrLK
Line causing issue:
new_pts, ttl, err = cv2.calcOpticalFlowPyrLK(self.old_img, i_img, i_old_pts, None)
Does anyone have any idea where I can begin debugging this?
Answer
I had the same problem when I did optical flow based tracking. I tried many many different ways to solve this. But in vain.
Finally, there was an example program in which they tracked using shi-tomsi corner points detection and those points were used in the LK algorithm and it worked perfectly. So i probed into the data types and dimensions of the output of the Shi-Tomsi detector and I made sure my points to be tracked were of the same type. It woked!
Here's what you need to know.
- make sure the images are grayscale.
- your coordinate parameter that is i_old_pts should be single precision float meaning float32. This type is available in numpy use that. the float in python is float64
- the coordinate parameter i_old_pts(from your program) should be a numpy array with the dimension (n,1,2) where n represents the number of points.
This should work.