@inproceedings{393cde9df2f0414ab7724805b8509fe4,
title = "Region of interest growing neural gas for real-time point cloud processing",
abstract = "This paper proposes a real-time topological structure learning method based on concentrated/distributed sensing for a 2D/3D point cloud. First of all, we explain a modified Growing Neural Gas with Utility (GNG-U2) that can learn the topological structure of 3D space environment and color information simultaneously by using a weight vector. Next, we propose a Region Of Interest Growing Neural Gas (ROI-GNG) for realizing concentrated/distributed sensing in real-time. In ROI-GNG, the discount rates of the accumulated error and utility value are variable according to the situation. We show experimental results of the proposed method and discuss the effectiveness of the proposed method.",
keywords = "Growing Neural Gas, Point cloud processing, Topological structure learning",
author = "Yuichiro Toda and Xiang Li and Takayuki Matsuno and Mamoru Minami",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
year = "2019",
doi = "10.1007/978-3-030-27535-8_8",
language = "English",
isbn = "9783030275341",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "82--91",
editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Yuwang Liu and Zhaojie Ju and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings",
}