Contextual Analysis Of Tactical Scenes

Arthur V. Forman Jr.; Patricia J. Rowland; Wade G. Pemberton

doi:10.1117/12.943184

14 June 1984 Contextual Analysis Of Tactical Scenes

Arthur V. Forman Jr., Patricia J. Rowland, Wade G. Pemberton

Proceedings Volume 0485, Applications of Artificial Intelligence I; (1984) https://doi.org/10.1117/12.943184
Event: 1984 Technical Symposium East, 1984, Arlington, United States

Abstract

Current automated approaches for recognizing spatially localized objects fall short of human recognition performance for two reasons. First, the classical statistical pattern recognizer uses only locally measured scene information in the recognition process. Contextual information can and should be extracted and exploited to enhance automated statistical approaches. Second, the human recognizer is able to learn from and adapt to new situations, while the automatic statistical pattern recognizer is confounded by any object that fails to match some subset of its training experience. Techniques from artificial intelligence can be employed to endow the machine with the ability to adapt to the scene at hand based on feedback of derived scene information. This paper describes an intelligent automated object recognition system that uses extracted scene context and feedback for improved recognition.

Citation Download Citation

Arthur V. Forman Jr., Patricia J. Rowland, and Wade G. Pemberton "Contextual Analysis Of Tactical Scenes", Proc. SPIE 0485, Applications of Artificial Intelligence I, (14 June 1984); https://doi.org/10.1117/12.943184

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available