A 3D shape constraint on video

Author

Ji, Hui ; Fermuller, Cornelia

Author_Institution

Center for Autom. Res., Maryland Univ., College Park, MD, USA

Volume

28

Issue

6

fYear

2006

fDate

6/1/2006 12:00:00 AM

Firstpage

1018

Lastpage

1023

Abstract

We propose to combine the information from multiple motion fields by enforcing a constraint on the surface normals (3D shape) of the scene in view. The fact that the shape vectors in the different views are related only by rotation can be formulated as a rank = 3 constraint. This constraint is implemented in an algorithm which solves 3D motion and structure estimation as a practical constrained minimization. Experiments demonstrate its usefulness as a tool in structure from motion providing very accurate estimates of 3D motion.

Keywords

minimisation; motion estimation; video signal processing; 3D motion estimation; multiple motion fields; practical constrained minimization; shape vectors; structure estimation; surface normals; video 3D shape constraint; Cameras; Estimation error; Fluid flow measurement; Image reconstruction; Layout; Minimization methods; Motion estimation; Parameter estimation; Shape; Stability; Three-dimensional motion estimation; decoupling translation from rotation; integration of motion fields; shape and rotation.; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Pattern Recognition, Automated; Photography; Video Recording;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/TPAMI.2006.109

Filename

1624366