Gaze-Based Activity Recognition with a LSTM

Classification of sedentary activities using gaze tracking data can be of great use in fields such as teaching, human-computer interaction and surveilling. Conventional machine learning methods such as k-nearest neighbours, random forest and support vector machine might be used to classify such activities, but this requires knowledge about the...