Paper
24 September 2011 Uniformly spaced 3D modeling of human face from two images using parallel particle swarm optimization
Yau-Zen Chang, Jung-Fu Hou, Yi Hsiang Tsao, Shih-Tseng Lee
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Abstract
This paper proposes a scheme for finding the correspondence between uniformly spaced locations on the images of human face captured from different viewpoints at the same instant. The correspondence is dedicated for 3D reconstruction to be used in the registration procedure for neurosurgery where the exposure to projectors must be seriously restricted. The approach utilizes structured light to enhance patterns on the images and is initialized with the scale-invariant feature transform (SIFT). Successive locations are found according to spatial order using a parallel version of the particle swarm optimization algorithm. Furthermore, false locations are singled out for correction by searching for outliers from fitted curves. Case studies show that the scheme is able to correctly generate 456 evenly spaced 3D coordinate points in 23 seconds from a single shot of projected human face using a PC with 2.66 GHz Intel Q9400 CPU and 4GB RAM.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yau-Zen Chang, Jung-Fu Hou, Yi Hsiang Tsao, and Shih-Tseng Lee "Uniformly spaced 3D modeling of human face from two images using parallel particle swarm optimization", Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 81351P (24 September 2011); https://doi.org/10.1117/12.892066
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
3D modeling

Particle swarm optimization

Particles

Image registration

Projection systems

3D image processing

Structured light

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