Computational Model of Visual Interpretation
Masters Thesis | Kaustuv De Biswas | Massachusetts Institute of Technology
Committee: Prof. Terry Knight | Prof. George Stiny | Prof. Patrick Winston

 
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From the very early phases of design conception, designers use sketches as a powerful design tool. Sketches are however ambiguous. Meanings are associated on fly as the designer ‘comes up' with certain ideas while working with it. There is no hierarchy in a sketch. In fact ‘structure' is established only after meanings are applied to the sketch. However even in such structurally and conceptually fluid territory, the designer solves most of his design problems and very often comes to quick resolutions. To understand this fascinating tool and how the designer interacts with it, we need to understand how we visually interpret sketches.

The process of design is also a reflective act. The designer keeps changing his perspectives and focus based on the unexpected opportunities that emerge from such reflection. Computational systems used today in design exploration are not capable of doing so. On the contrary these systems model the world in a very rigid structured way and cannot produce design ideas beyond what their preset description anticipates. From this perspective there is no novelty‚ or surprise‚ in such systems.

As a step forward, this thesis proposes the following:

1. Visual Schemas as procedural units of visual memory. They schematically store real world knowledge ('courtyard') and form the basis for interpretation.

2. Separation of Shape and Visual Concepts. This thesis suggests that shapes are flat and abstract collection of parts, while visual concepts are subjective and hierarchic ideas, which are formed from the shapes through interpretation.

A LISP machine is presented as a basic computational framework for implementing and establishing the model that is proposed. It observes a relatively simple architectural sketch, interprets it reflectively through the activation of potential, alternative contexts, and then gives a collection of concepts that it manages to ‘see' in the sketch.

last update March 13 @Kaustuv Kanti De Biswas