Image-based Modeling by Minimizing Projection Error of Primitive Edges


The KIPS Transactions:PartB , Vol. 12, No. 5, pp. 567-576, Oct. 2005
10.3745/KIPSTB.2005.12.5.567,   PDF Download:

Abstract

This paper proposes an image-based modeling method which recovers 3D models using projected line segments in multiple images. Using the method, a user obtains accurate 3D model data via several steps of simple manual works. The embedded nonlinear minimization technique in the model parameter estimation stage is based on the distances between the user provided image line segments and the projected line segments of primitives. We define an error using a finite line segment and thus increase accuracy in the model parameter estimation. The error is defined as the sum of differences between the observed image line segments provided by the user and the predicted image line segments which are computed using the current model parameters and camera parameters. The method is robust in a sense that it recovers 3D structures even from partially occluded objects and it does not be seriously affected by small measurement errors in the reconstruction process. This paper also describesexperimental results from real images and difficulties and tricks that are found while implementing the image-based modeler.


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Cite this article
[IEEE Style]
J. S. Park, "Image-based Modeling by Minimizing Projection Error of Primitive Edges," The KIPS Transactions:PartB , vol. 12, no. 5, pp. 567-576, 2005. DOI: 10.3745/KIPSTB.2005.12.5.567.

[ACM Style]
Jong Seung Park. 2005. Image-based Modeling by Minimizing Projection Error of Primitive Edges. The KIPS Transactions:PartB , 12, 5, (2005), 567-576. DOI: 10.3745/KIPSTB.2005.12.5.567.