Real-Time Scene Understanding And Vision Automation--A Brief Overview

Jack Sklansky; K. H. Kim

doi:10.1117/12.940013

30 April 1987 Real-Time Scene Understanding And Vision Automation--A Brief Overview

Jack Sklansky, K. H. Kim

Proceedings Volume 0755, Image Pattern Recognition: Algorithm Implementations, Techniques, and Technology; (1987) https://doi.org/10.1117/12.940013
Event: OE LASE'87 and EO Imaging Symposium, 1987, Los Angeles, CA, United States

Abstract

After about twenty-five years of growth, image analysis technology has advanced to the point where the design of machines that model real scenes in real time is at the technological frontier. Consequently, we see the beginning of a merging of the technologies of image analysis and automatic control. This merger is leading to the development of complex distributed systems in which decisions and actions are based on realistic models of possibly time-varying scenes. We refer to this merged technology as vision automation. In the past decade, reflecting the impact of artificial intelligence, image analysis has expanded to scene understanding, and automatic control has evolved into intelligent control. Thus, vision automation consists of two major components: scene understanding and intelligent control. (We prefer the term "scene understanding" to the more commonly used "image understanding", since we want to understand the scene, not the image.)

Citation Download Citation

Jack Sklansky and K. H. Kim "Real-Time Scene Understanding And Vision Automation--A Brief Overview", Proc. SPIE 0755, Image Pattern Recognition: Algorithm Implementations, Techniques, and Technology, (30 April 1987); https://doi.org/10.1117/12.940013

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