N-dimension closeness measurements used in dynamic pattern recognitions

Chialun John Hu

doi:10.1117/12.837107

18 January 2010 N-dimension closeness measurements used in dynamic pattern recognitions

Chialun John Hu

Proceedings Volume 7539, Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques; 75390U (2010) https://doi.org/10.1117/12.837107
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

When a standard ND (N-dimension) curve is compared to a test ND curve, the Euclidean distance between these two curves is defined as the root-mean-square sum of the distances between each (test) point in the test curve and the point on the standard curve closest to that test point. This number of root-mean-square sum is called the closeness CLS of the test curve to the standard curve in the ND state space where each point in the space may represent a snap shot of a certain moving or time-varying object. This CLS number can be used to identify accurately, a test moving object against several standard moving objects stored in the memory of this dynamic pattern recognition system, according to the particular way each standard object moves. In this paper, we use the face recognition scheme as a particular example that leads to the general analysis and design procedure.

Citation Download Citation

Chialun John Hu "N-dimension closeness measurements used in dynamic pattern recognitions", Proc. SPIE 7539, Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques, 75390U (18 January 2010); https://doi.org/10.1117/12.837107

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