US 12,455,162 B2
Three-dimensional shape measuring method and three-dimensional shape measuring apparatus
Hidechika Ito, Sendai (JP); Shingo Kagami, Sendai (JP); Koichi Hashimoto, Sendai (JP); Daichi Suzuki, Tachikawa (JP); Yoshiyuki Toso, Toyokawa (JP); and Yoshihiro Inagaki, Hachioji (JP)
Assigned to Konica Minolta, Inc., Tokyo (JP); and Tohoku University, Miyagi (JP)
Filed by Tohoku University, Miyagi (JP); and Konica Minolta, Inc., Tokyo (JP)
Filed on Dec. 5, 2022, as Appl. No. 18/075,026.
Claims priority of application No. 2021-197429 (JP), filed on Dec. 6, 2021.
Prior Publication US 2023/0175840 A1, Jun. 8, 2023
Int. Cl. G01B 11/25 (2006.01); G06T 7/521 (2017.01); G06T 7/55 (2017.01)
CPC G01B 11/25 (2013.01) [G06T 7/521 (2017.01); G06T 7/55 (2017.01)] 10 Claims
OG exemplary drawing
 
9. A three-dimensional (3D) shape measuring method comprising:
a first step to:
project, with a projector, first and second projection images on a target object, wherein the first projection images include row-direction stripe patterns different from each other, and the second projection images include column-direction stripe patterns different from each other, and
obtain, with an image capturing device, first and second captured images of the target object, wherein the first captured images are captured while the first projection images are projected, and the second captured images are captured while the second projection images are projected;
a second step to identify a corresponding projection pixel of the first and second projection images, wherein the corresponding projection pixel corresponds to each of captured pixels of the first and second captured images; and
a third step to identify a 3D shape of the target object based on a result of the second step, wherein
the second step comprises:
identifying a corresponding pixel row that corresponds to each of the captured pixels from among projection pixel rows constituting the first projection images, based on the first captured images and the row-direction stripe patterns;
identifying a corresponding pixel column that corresponds to each of the captured pixels from among projection pixel columns constituting the second projection images, based on the second captured images and the column-direction stripe patterns;
identifying a candidate projection pixel that is at an intersection of the corresponding pixel row and the corresponding pixel column and that satisfies an epipolar constraint; and
identifying the corresponding projection pixel from the candidate projection pixel, and the second step further comprises:
identifying a light transport matrix (LTM) that describes corresponding pixel rows each of which is the corresponding pixel row by applying sparse optimization, based on the first captured images and the row-direction stripe patterns; and
identifying an LTM that describes corresponding pixel columns each of which is the corresponding pixel column by applying sparse optimization, based on the second captured images and the column-direction stripe patterns.