Human gesture recognition via bag of angles for 3D virtual city planning in CAVE environment

Cave Automatic Virtual Environment (CAVE) provides an immersive virtual environment for 3D city planning. However, the user in the cave has to wear wearable markers for the interaction with the 3D models. To develop a natural interaction, depth camera like Kinect has to be considered. In this paper, we propose a new skeleton joint representation called Bag of Angles (BoA) for human gesture recognition. We evaluated our proposed BoA representation on two dataset UTD-MHAD and UTD-MHAD-KinectV2. The evaluation results demonstrated that the proposed BoA representation can achieve a higher recognition accuracy compared to the other existing representation methods.