As I haven’t yet created a permanent place to hold the dataset I collected for my most recent class project, I’m hanging it here for now. SLANG-3k is an uncurated corpus of 3000 clips of 15 seconds each of people signing in American Sign Language, British Sign Language, and German Sign Language, intended as a public benchmark dataset for sign language identification in the wild. Using 5 frames, I was able to achieve accuracies bounded around 0.66/0.67. More details can be found in the paper and poster created for CS 231N, Convolutional Neural Networks for Visual Recognition.
Many thanks to everyone who helped with this project — and most especially to the anonymous survey respondents who received only warm fuzzies as compensation for taking the time to help with this early-stage research.