Machine vision and appearance based learning

Alexander Bernstein

doi:10.1117/12.2268723

17 March 2017 Machine vision and appearance based learning

Alexander Bernstein

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 103411O (2017) https://doi.org/10.1117/12.2268723
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

Abstract

Smart algorithms are used in Machine vision to organize or extract high-level information from the available data. The resulted high-level understanding the content of images received from certain visual sensing system and belonged to an appearance space can be only a key first step in solving various specific tasks such as mobile robot navigation in uncertain environments, road detection in autonomous driving systems, etc. Appearance-based learning has become very popular in the field of machine vision. In general, the appearance of a scene is a function of the scene content, the lighting conditions, and the camera position. Mobile robots localization problem in machine learning framework via appearance space analysis is considered. This problem is reduced to certain regression on an appearance manifold problem, and newly regression on manifolds methods are used for its solution.

Citation Download Citation

Alexander Bernstein "Machine vision and appearance based learning", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411O (17 March 2017); https://doi.org/10.1117/12.2268723

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