機械学習による3次元CGモデル直接描画の推測

カテゴリ: 全国大会

論文No: 4-161

グループ名: 【全国大会】令和6年電気学会全国大会論文集

発行日: 2024/03/01

タイトル(英語): Presumption of 3D Direct Drawing Compute Graphic Model using Machine Learning

著者名: 三橋郁（帝京大学）

著者名(英語): Kaoru Mitsuhashi (Teikyo University)

キーワード: AR技術|3次元直接描画|機械学習|Augmented Reality|3D direct drawing|machine learning

要約(日本語): The 3D direct drawing system can create the point, the segment, the polygonal and curved surface, and the solid model. However, creating the model is difficult for a user because the command is multiple and complicated. In this paper, the drawing trends and trajectories are investigated. After that, they are predicted and converted to the desired shape using Neural Network method, k-Nearest Neighbor method, and Support Vector Machine method of machine learning, and the accuracy rates of the two methods are compared.

本誌掲載ページ: 269-271 p

原稿種別: 日本語

PDFファイルサイズ: 573 Kバイト