Facial feature tracking with the super image vector inner product

Wei Su; Laurence G. Hassebrook; S. Hariharan

doi:10.1117/12.719615

7 May 2007 Facial feature tracking with the super image vector inner product

Wei Su, Laurence G. Hassebrook, S. Hariharan

Proceedings Volume 6566, Automatic Target Recognition XVII; 656618 (2007) https://doi.org/10.1117/12.719615
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

We overview a technique known as Super Image Vector Inner Product as applied to Facial pose estimation. The method is mathematically similar to correlation based methods but is numerically more efficient. The Vector Inner Product approach attains its pose and position estimation by embedding these distortions in its phase response. We demonstrate for the first time, that that the Super Image Vector Inner Product can be used for facial identification. We present a method by which segmenting the face into a set of feature regions, individual Super Images can be combined together using mesh techniques to track facial expressions.

Citation Download Citation

Wei Su, Laurence G. Hassebrook, and S. Hariharan "Facial feature tracking with the super image vector inner product", Proc. SPIE 6566, Automatic Target Recognition XVII, 656618 (7 May 2007); https://doi.org/10.1117/12.719615

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