Progress
This week I made an OpenCV example using the old Intel RealSense L515 (which should also work for the new Intel Realsense D455). I used Haar cascades (the most common method) to detect faces using the RGB camera that the Intel Realsense device comes with. I used both a frontal and profile cascade (so if it cannot detect a frontal face, it can use the profile face). I also looked into the different methods for face detection. These methods are clearly described in this link. I think using OpenCV’s DNN module might be better for our project, as it is more accurate, so I might make an example of that next week. The DNN model might be less accurate based on the training set though, so I will look for a representative training dataset online. In case we want to make the OpenCV process even faster, I found a C++ library that runs OpenCV faster by using different SIMD CPU extensions that I might try to use in the future to use if/after MVP is reached. My example can be found in our team repository.
Schedule
I believe as of now, our progress is on schedule.
Next Steps
Over the next week, I’ll try to get a DNN example going. More importantly, I will write the Design Review Report with my group members that is due next Friday.