Superquadrics-based object representation of complex scenes from range images

Yan Zhang; Jeffery R. Price; Mongi A. Abidi

doi:10.1117/12.424914

13 April 2001 Superquadrics-based object representation of complex scenes from range images

Yan Zhang, Jeffery R. Price, Mongi A. Abidi

Proceedings Volume 4298, Three-Dimensional Image Capture and Applications IV; (2001) https://doi.org/10.1117/12.424914
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

This paper investigates the superquadrics-based object representation of complex scenes from range images. The issues on how the recover-and-select algorithm is incorporated to handle complex scenes containing background and multiple occluded objects are addressed respectively. For images containing backgrounds, the raw image is first coarsely segmented using the scan-line grouping technique. An area threshold is then taken to remove the backgrounds while keeping all the objects. After this pre-segmentation, the recover-and-select algorithm is applied to recover superquadric (SQ) models. For images containing multiple occluded objects, a circle-view strategy is taken to recover complete SQ models from range images in multiple views. First, a view path is planned as a circle around the objects, on which images are taken approximately every 45 degrees. Next, SQ models are recovered from each single-view range image. Finally, the SQ models from multiple views are registered and integrated. These approaches are tested on synthetic range images. Experimental results show that accurate and complete SQ models are recovered from complex scenes using our strategies. Moreover, the approach handling background problems is insensitive to the pre-segmentation error.

Citation Download Citation

Yan Zhang, Jeffery R. Price, and Mongi A. Abidi "Superquadrics-based object representation of complex scenes from range images", Proc. SPIE 4298, Three-Dimensional Image Capture and Applications IV, (13 April 2001); https://doi.org/10.1117/12.424914

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