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Proceedings Paper

Eye for design: why, where, and how to look for causal structure in visual scenes
Author(s): Matthew Brand
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Paper Abstract

Before addressing the problem of visual recognition, we need to understand what the result of visual cognition is: What is new in memory after a scene has been understood? For an agent that is to interact with the scene, the most important result of visual understanding is an analysis of the causal structure of the scene: How motion is originated, constrained, and prevented, and what will happen in the immediate future. With respect to the agent's goals, such an understanding describes the scene in terms of its functional properties -- how the agent may interact with the scene. In order to arrive at such an understanding, a robot must have a sophisticated theory of how the world is designed. We discuss some of the consequences of this view for the construction of purposeful vision systems, and show examples from our own work in the understanding of complex scenes.

Paper Details

Date Published: 1 November 1992
PDF: 9 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131526
Show Author Affiliations
Matthew Brand, Northwestern Univ. (United States)


Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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