3D Modelling Using Machine Learning Technique

The objective of this project is to perform 3D modeling using machine learning techniques, extensive research on 3D modeling and machine learning techniques were conducted. Machine learning methods are classified as the image rending-based methods, it has the features of low cost, flexible in applic...

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書目詳細資料
主要作者: Zhao, Haolong
其他作者: Huang Guangbin
格式: Final Year Project
語言:English
出版: 2018
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在線閱讀:http://hdl.handle.net/10356/75556
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機構: Nanyang Technological University
語言: English
實物特徵
總結:The objective of this project is to perform 3D modeling using machine learning techniques, extensive research on 3D modeling and machine learning techniques were conducted. Machine learning methods are classified as the image rending-based methods, it has the features of low cost, flexible in application, easy to set up, which are desired in most of the application scenarios. In-depth study and testing of 3D-R2N2 network is also carried out. LSTM, CNN networks are studied during the process of understand the network structure of 3D-R2N2. As well as dataset preparations including image rendering and voxel grid, which are fundamental steps of machine learning works. Test Results of two dataset, ShapeNet used in previous, and ModelNet40, extra dataset rendered in this project are shown and discussed in the report, too. Basically, 3D reconstruction faces many challenges like self-occlusion, tilted viewing angle, those intrinsic obstacles makes 3D reconstruction using machine learning a very challenging.