Pose estimation in automatic object recognition

C. Y. Chang; Richard Hoepner

doi:10.1117/12.235655

15 March 1996 Pose estimation in automatic object recognition

C. Y. Chang, Richard Hoepner

Proceedings Volume 2752, Optical Pattern Recognition VII; (1996) https://doi.org/10.1117/12.235655
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

Significant problems with a standard shape based approach to object pose estimation are the size of the database needed and the time it takes to search this database. The problems are compounded with highly symmetric objects whose internal detail must be considered for accurate pose determination. Our approach to object pose estimation is based on the reciprocal basis image set. The method is related to the one that uses a suite of gray-scale images of object for analytical object model representation. By representing the object as a Fourier series using a finite sample set of poses, the object model consisting of a reciprocal basis image set can be determined. When an input image is projected onto the reciprocal image basis, an estimate for the object pose can be obtained from the phase of a complex exponential. This allows a suite of images rotated about an axis to be represented by a reciprocal basis image set. Pose estimation about this axis can then be determined by a linear projection of the input object onto this reciprocal basis. The internal detail of the image is thus maintained through a finite reciprocal basis image set, allowing for accurate post estimation of highly symmetric objects. This method can decrease both computation time and disk space from many standard shape based approaches. Examples illustrating the highly accurate performance of object pose estimation using synthetic armor images based on the reciprocal basis approach are given.

Citation Download Citation

C. Y. Chang and Richard Hoepner "Pose estimation in automatic object recognition", Proc. SPIE 2752, Optical Pattern Recognition VII, (15 March 1996); https://doi.org/10.1117/12.235655

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image compression

Image processing

Databases

Wavelets

Error analysis

Image analysis

Object recognition

Show All Keywords

Keywords/Phrases

Search In:

Publication Years