A novel curved gaussian mixture model and its application in motion skill encoding
(2021)
Conference Proceeding
Chen, D., Li, G., Zhou, D., & Ju, Z. (2021). A novel curved gaussian mixture model and its application in motion skill encoding. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (7813-7818). https://doi.org/10.1109/IROS51168.2021.9636121
The purpose of this paper is to present a novel curved Gaussian Mixture Model (CGMM) and to study the application of it in motion skill encoding. Primarily, Gaussian mixture model (GMM) has been widely applied on many occasions when a probability den... Read More about A novel curved gaussian mixture model and its application in motion skill encoding.