Machines' perception of space
Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2018.
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis |
Language: | eng |
Published: |
Massachusetts Institute of Technology
2018
|
Subjects: | |
Online Access: | http://hdl.handle.net/1721.1/118574 |
_version_ | 1811093164803489792 |
---|---|
author | Peng, Wenzhe |
author2 | Takehiko Nagakura. |
author_facet | Takehiko Nagakura. Peng, Wenzhe |
author_sort | Peng, Wenzhe |
collection | MIT |
description | Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2018. |
first_indexed | 2024-09-23T15:40:42Z |
format | Thesis |
id | mit-1721.1/118574 |
institution | Massachusetts Institute of Technology |
language | eng |
last_indexed | 2024-09-23T15:40:42Z |
publishDate | 2018 |
publisher | Massachusetts Institute of Technology |
record_format | dspace |
spelling | mit-1721.1/1185742019-04-11T05:37:30Z Machines' perception of space Peng, Wenzhe Takehiko Nagakura. Massachusetts Institute of Technology. Department of Architecture. Massachusetts Institute of Technology. Department of Architecture. Architecture. 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. 2018-10-15T20:25:53Z 2018-10-15T20:25:53Z 2018 2018 Thesis http://hdl.handle.net/1721.1/118574 1055766556 eng 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 108 pages application/pdf Massachusetts Institute of Technology |
spellingShingle | Architecture. Peng, Wenzhe Machines' perception of space |
title | Machines' perception of space |
title_full | Machines' perception of space |
title_fullStr | Machines' perception of space |
title_full_unstemmed | Machines' perception of space |
title_short | Machines' perception of space |
title_sort | machines perception of space |
topic | Architecture. |
url | http://hdl.handle.net/1721.1/118574 |
work_keys_str_mv | AT pengwenzhe machinesperceptionofspace |