Project
Measuring the Immeasurable: An Experiment for a Machine to Map Low-Level

Yuxuan Liu
SMArchS Thesis, Computation
Advisor: Takehiko Nagakura
Reader: Axel Kilian

Constructing experience is an important part in architectural design, and experience-oriented design is highly dependent on an architect's subjective understanding of space. Although design and computer science have become more closely integrated in recent years, commercialized computer-aided design (CAD) systems are still only able to substitute labor-intensive processes, such as auto-generation of architectural drawings from digital models but offer little support in actual design. The human-centric design process is still not yet substitutable by non-human system, due to non-human system’s lack of the ability to understand space subjectively.

This thesis’ focus is on developing machine awareness of space. The research method is on translating human-level spatial awareness represented by adjectives in language to a non-human system through single shot architectural photo based on a data-driven machine learning method. As humans show general consistency in subjective understanding of space, experiments are designed and published on crowd-sourcing platform Amazon Mechanical Turk (AMT) to match architectural space represented in single shot photo with subjective understanding of it represented by adjectives in language. These collected data will assist the development of a machine system. The completed proposed system employs techniques such as 3D geometry reconstruction from a single image, surface simplification, scene attributes extraction, color vividness extraction, vocabulary classification in order to understand low-level features of space. This low-level understanding is then translated to the likeliest high-level, text-based understanding by the machine system based on a data-driven machine learning method.

As in this thesis, adjectives are regarded as the signal of human’s subjective understanding of space, it also explores the subjective mental process in people’s mind of decoding the space’s nature through text-based representation. If we consider design as sophisticated mental mechanism that manipulates multiple information and space is the key element in this phase, a deeper understanding of space will definitely help us to design better.