Progress
I have some bits and pieces in cascade.py (work can be found on the team repository) that are related to tinkering with OpenCV and super resolution, but nothing related to it that resulted in something concrete. This week I mainly just focused on finding the distance of a face’s chin by combining information from the depth and color frames. First I had to align the depth and color frames, and this kind of confused me because the shape of the numpy vector from the depth frame was consistently (480, 848), which is a far cry from the resolution we were expecting (1280 x 720). Then, using calculations shown here, I calculated the angle of each pixel, and using the number of pixels the person was away from the center, I calculated the x, y distance of the person from the camera. Essentially I have finished an elementary version of the User Position Extraction.
Schedule
So far my progress is roughly on schedule.
Next Steps
Next week, I hope to work with Dianne in integrating the LAOE algorithm and the User Position Extraction, and seeing if the results seem reasonable. If time and weather allow for it, I’d like to try testing this integration.