Seeing physics, or: physics is for prediction

Matthew Brand*, Paul Cooper, Lawrence Birnbaum

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

We describe how knowledge of the physics of the scene itself is important to computer vision. High-level knowledge of scene physics can help programs see the world, and programs that see and understand this way are useful for planning plan scene interactions. We illustrate these points with two of our most recent knowledge-intensive vision systems. One uses knowledge of physics and function to understand noisy and ambiguous images of gear-train machines; i.e. to report what the machine does. The other uses physical knowledge to guide a robotic eye-hand system to pick up a mug of coffee by its handle.

Original languageEnglish (US)
Title of host publicationProc Workshop Phys Based Model Computer Vision
Editors Anon
PublisherIEEE
Pages144-150
Number of pages7
StatePublished - Jan 1 1995
EventProceedings of the Workshop on Physics-Based Modeling in Computer Vision - Cambridge, MA, USA
Duration: Jun 18 1995Jun 19 1995

Other

OtherProceedings of the Workshop on Physics-Based Modeling in Computer Vision
CityCambridge, MA, USA
Period6/18/956/19/95

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Brand, M., Cooper, P., & Birnbaum, L. (1995). Seeing physics, or: physics is for prediction. In Anon (Ed.), Proc Workshop Phys Based Model Computer Vision (pp. 144-150). IEEE.