Paper
25 September 2001 Curve evolution and 3D reconstruction
Hongchuan Yu, Dejun Wang, Zesheng Tang, Long Tang
Author Affiliations +
Proceedings Volume 4553, Visualization and Optimization Techniques; (2001) https://doi.org/10.1117/12.441585
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
Abstract
In this paper, we apply the geometric curve evolution approach to 3D reconstruction for a number of images in the stereo vision. The curve evolution approach is based on the Euclidean curve shortening evolution theory, and the level set method is introduced into it for numerical computation. The Euler-Lagrange equations that are deduced from the variational principle provide a set of curve evolving equations. These PDE's describe the process of the geometric curve evolution on the relevant epipolar plane. In 3D space, the each epipolar plane is monogamously projected as a unique pair of the intra-scanlines on stereo pairs. These PDE's are used to deform an initial set of curves that then move towards the object outlines to be detected. The level set implementation of these PDE's provides an efficient and robust computational way for the kind of the geometric-driven evolving equations. The velocity term in the level set equations can be obtained from the above geometric curve evolving equations. It is intrinsic and only depends upon the stereo problem. We present the close form of the velocity. Finally, the results of implementation of our theory are presented on synthetic images.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongchuan Yu, Dejun Wang, Zesheng Tang, and Long Tang "Curve evolution and 3D reconstruction", Proc. SPIE 4553, Visualization and Optimization Techniques, (25 September 2001); https://doi.org/10.1117/12.441585
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KEYWORDS
Gold

3D modeling

3D vision

Cameras

Computer science

Computer vision technology

Image segmentation

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