TY - GEN
T1 - Dispersed Structured Light for Hyperspectral 3D Imaging
AU - Shin, Suhyun
AU - Choi, Seokjun
AU - Heide, Felix
AU - Baek, Seung Hwan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Hyperspectral 3D imaging aims to acquire both depth and spectral information of a scene. However, existing methods are either prohibitively expensive and bulky or compromise on spectral and depth accuracy. In this paper, we present Dispersed Structured Light (DSL), a cost-effective and compact method for accurate hyperspectral 3D imaging. DSL modifies a traditional projectorcamera system by placing a sub-millimeter thick diffraction grating film front of the projector. This configuration enables dispersing structured light based on light wavelength. To utilize the dispersed structured light, we devise a model for dispersive projection image formation and a per-pixel hyperspectral 3D reconstruction method. We validate DSL by instantiating a compact experimental prototype. DSL achieves spectral accuracy of 18.8 nm full-width half-maximum (FWHM) and depth error of 1 mm, outperforming prior work on practical hyperspectral 3D imaging. DSL promises accurate and practical hyperspectral 3D imaging for diverse application domains, including computer vision and graphics, cultural heritage, geology, and biology.
AB - Hyperspectral 3D imaging aims to acquire both depth and spectral information of a scene. However, existing methods are either prohibitively expensive and bulky or compromise on spectral and depth accuracy. In this paper, we present Dispersed Structured Light (DSL), a cost-effective and compact method for accurate hyperspectral 3D imaging. DSL modifies a traditional projectorcamera system by placing a sub-millimeter thick diffraction grating film front of the projector. This configuration enables dispersing structured light based on light wavelength. To utilize the dispersed structured light, we devise a model for dispersive projection image formation and a per-pixel hyperspectral 3D reconstruction method. We validate DSL by instantiating a compact experimental prototype. DSL achieves spectral accuracy of 18.8 nm full-width half-maximum (FWHM) and depth error of 1 mm, outperforming prior work on practical hyperspectral 3D imaging. DSL promises accurate and practical hyperspectral 3D imaging for diverse application domains, including computer vision and graphics, cultural heritage, geology, and biology.
KW - Hyperspectral 3D Imaging
UR - https://www.scopus.com/pages/publications/85212882379
UR - https://www.scopus.com/pages/publications/85212882379#tab=citedBy
U2 - 10.1109/CVPR52733.2024.02361
DO - 10.1109/CVPR52733.2024.02361
M3 - Conference contribution
AN - SCOPUS:85212882379
SN - 9798350353006
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 24997
EP - 25006
BT - Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024
PB - IEEE Computer Society
T2 - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024
Y2 - 16 June 2024 through 22 June 2024
ER -