2026-09-18T17:33:33Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1185742022-01-13T07:53:53Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Takehiko Nagakura.
Peng, Wenzhe
Massachusetts Institute of Technology. Department of Architecture.
Massachusetts Institute of Technology. Department of Architecture
2018-10-15T20:25:53Z
2018-10-15T20:25:53Z
2018
2018
http://hdl.handle.net/1721.1/118574
1055766556
Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 106-108).
Architectural design is highly dependent on the architect's understanding of space. However, in the era of digital revolution, when efficiency and economy are the major concerns in most industrial fields, whether a computer can gain human-like understanding to read and operate space and assist with its design and analysis remains a question. This thesis focuses on the geometrical aspects of spatial awareness. Machine systems that have similar behaviors to humans' perceptions of space in geometric aspects will be developed employing techniques such as isovist and machine learning, and trained with open-sourced datasets, self-generated datasets or crowdsourced datasets. The proposed systems simulate behaviors including space composition classification, space scene classification, 3D reconstruction of space, space rating and algebraic operations of space. These aspects cover topics ranging from pure geometrical understandings to semantic reasoning and emotional feelings of space. The proposed systems are examined in two ways. Firstly, they are applied to a real-time space evaluation modeling interface, which gives a user instant insights about the scene being constructed; Secondly, they are also undertaken in the spatial analysis of existing architectural designs, namely small designs by Mies van der Rohe and Aldo van Eyck. The case studies conducted validate that this methodology works well in understanding local spatial conditions, and that it can be helpful either as a design aid tool or in spatial analysis.
by Wenzhe Peng.
S.M.
108 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Architecture.
Machines' perception of space
Thesis
application/pdf
Publication
unknown
unknown
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