  This paper proposes a human activity recognition method which is based on
features learned from 3D video data without incorporating domain knowledge. The
experiments on data collected by RGBD cameras produce results outperforming
other techniques. Our feature encoding method follows the bag-of-visual-word
model, then we use a SVM classifier to recognise the activities. We do not use
skeleton or tracking information and the same technique is applied on color and
depth data.
