Three-dimensional model-based object recognition and pose estimation using probabilistic principal surfaces

Kui-yu Chang; Joydeep Ghosh

doi:10.1117/12.382913

14 April 2000 Three-dimensional model-based object recognition and pose estimation using probabilistic principal surfaces

Kui-yu Chang, Joydeep Ghosh

Author Affiliations +

Proceedings Volume 3962, Applications of Artificial Neural Networks in Image Processing V; (2000) https://doi.org/10.1117/12.382913
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

A novel scheme using spherical manifolds is proposed for the simultaneous classification and pose estimation of 3D objects from 2D images. The spherical manifold imposes a local topological constraint on samples that are close to each other, while maintaining a global structure. Each node on the spherical manifold also corresponds nicely to a pose on a viewing sphere with 2 degrees of freedom. The proposed system is applied to aircraft classification and pose estimation.

Citation Download Citation

Kui-yu Chang and Joydeep Ghosh "Three-dimensional model-based object recognition and pose estimation using probabilistic principal surfaces", Proc. SPIE 3962, Applications of Artificial Neural Networks in Image Processing V, (14 April 2000); https://doi.org/10.1117/12.382913

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