What we have done:
Claudia has written a script for taking photos using the webcam, and is in the midst of collecting photos to be used as training data. This involves taking ~100 photos of about 20 individuals each.
Avi has delved into neural network architecture design to figure out how to build the adversarial network. The current plan is to use part of the architecture from the OpenFace network so that the adversarial network can learn to identify the same important features, and then use an architecture similar to a GAN network to reconstruct a 96×96 image to input to the OpenFace network. This is still in the process of being figured out. We hope to have three promising architectures to try set up by next week.
Dylan has been working on the calibration between the camera and the projector. For camera and projector lens distortion, we will correct for the lens distortion using the OpenCV fixing of lens distortion. Instead of correcting for distortion on the camera and then the projector, we are just going to calibrate them both since that seems to minimize error. We may not actually need to do much lens distortion fixing since we are only using the center of the photo and center of the projector where lens distortion is least. For finding the relationship between the camera and the projector, we will project chessboard corners with the projector and then use the solve for the homography matrix with ransac from OpenCV. Will test the camera projector calibration, but need to find a better way to project than mirroring displays.
What we are planning to do:
- Finish up design review presentation for Monday
- Research GAN network architectures