Vision-based terrain learning

Robert E. Karlsen; Gary Witus

doi:10.1117/12.664427

9 May 2006 Vision-based terrain learning

Robert E. Karlsen, Gary Witus

Proceedings Volume 6230, Unmanned Systems Technology VIII; 623005 (2006) https://doi.org/10.1117/12.664427
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

This paper presents an algorithm for online image-based terrain classification that mimics a human supervisor's segmentation and classification of training images into "Go" and "NoGo" regions. The algorithm identifies a set of image chips (or exemplars) in the training images that span the range of terrain appearance. It then uses the exemplars to segment novel images and assign a Go/NoGo classification. System parameters adapt to new inputs, providing a mechanism for learning. System performance is compared to that obtained via offline fuzzy c-means clustering and support vector machine classification.

Citation Download Citation

Robert E. Karlsen and Gary Witus "Vision-based terrain learning", Proc. SPIE 6230, Unmanned Systems Technology VIII, 623005 (9 May 2006); https://doi.org/10.1117/12.664427

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