The architecture of the program that is my capstone project is pretty simple so far. An input video is loaded. Then the program enters the main loop in which some processing will be done on/to each frame of that video. After processing, each frame of the video is displayed.
I’ve got the main loop set up and video frames loading in successfully, and have now started to implement some of the processing. The game board will tilt during play, but we want the computer to “see” the board as if it’s facing it head on during processing.
Here, I am in unknown territory as I don’t have previous experience with Computer Vision techniques. But with some direction from my project sponsor, Andrey, and from the OpenCV-Python documentation, I’ve learned that corners are great “features” to try to detect. So, first order of business is to try to detect the corners of the game board. From there, it should be relatively simple to adjust the perspective of the board in the video.
So, I naively attempt to run OpenCV-Python’s built-in Harris Corner detection algorithm. Detected corner should show up in red.
Uh oh… It’s detecting corners pretty much everywhere except where I need it to.
After some more investigation, it seems we may need to make some adjustments to the lighting or the camera settings so that the corners of our game board aren’t getting washed out. Andrey will be taking new videos with the adjusted lighting, and maybe next week I’ll have some extremely detected corners to show off.
