Region of Interest based Topological Structure Extraction using Growing Neural Gas for Environmental Recognition
Yuichiro Toda, Shin Miyake, Naoyuki Takesue, Kazuyoshi Wada, Naoyuki Kubota · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2016
In this paper, we propose a region of interest based topological structure extraction method for a 3D point cloud. Our method is based on Growing Neural Gas with Utility (GNG-U) for extracting the topological structure. GNG-U can apply to the non-stationary data distribution by using a local measurement value. However, GNG-U cannot control the number of nodes because GNG-U cannot reduce the number of nodes basically. Therefore, we propose the improved GNG-U for controlling the number of nodes. Next, we explain a feature extraction method using the topological structure. Furthermore, we propose the environmental recognition method based on central and peripheral vision. Finally, we show an experimental result, and discuss the effectiveness of the proposed method.