Live American Sign Language Letter Classification with Convolutional
  Neural Networks
Kyle Boone Ben Wurster Seth Thao Yu Hen Hu
This project is centered around building a neural network that is able to
recognize ASL letters in images, particularly within the scope of a live video
feed. Initial testing results came up short of expectations when both the
convolutional network and VGG16 transfer learning approaches failed to
generalize in settings of different backgrounds. The use of a pre-trained hand
joint detection model was then adopted with the produced joint locations being
fed into a fully-connected neural network. The results of this approach
exceeded those of prior methods and generalized well to a live video feed
application.