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24 September 2011Uniformly spaced 3D modeling of human face from two images using parallel particle swarm optimization
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.
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Yau-Zen Chang, Jung-Fu Hou, Yi Hsiang Tsao, 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