1. Introduce the structured light
Speaker: Chang-Hao Lin(林政豪)
Advisor: Dr. Pei-Ju Chiang (江佩如博士)

2. Projector-camera systems ↑
Abstract
3D scanning technology.
Passive methods and active methods.
Projector-camera system.
Projector-camera systems ↑

3. Abstract Coordinate systems. Pinhole camera Image coordinate
Homogeneous coordinate
Camera and world coordinate
Camera and world coordinate ↑
Image coordinate and camera coordinate ↑

4. Zhang’s camera calibration ↑
Intrinsic parameters
Extrinsic parameters
Distortion coefficients
Zhang’s camera calibration
OpenCV and Matlab toolbox
Zhang’s camera calibration ↑

5. Structured light system calibration↑
Projector calibration
Inverse camera
Local homography
Correspondence pixel between camera and projector
Stereo calibration
Rotation matrix and translation matrix between camera and projector
Structured light system calibration↑
Stereo calibration ↑

6. Gray code and line shifting patterns for 32-pixel-wide patterns
Structured light pattern
Time-multiplexing
Binary codes
Gray code + Phase shifting
Spatial Neighborhood
De Bruijn sequences
M-arrays
Direct coding
Binary code patterns ↑
Gray code and line shifting patterns for 32-pixel-wide patterns ↑

7. Image Processing Direct and global light components
Robust pixel classification
Adaptive threshold
𝑆= 𝐼 1 ,…, 𝐼 𝑘 is the selected set of pattern images, and 𝑝 is a valid pixel location, then the direct and global components at 𝑝, 𝐿 𝑑 𝑝 and 𝐿 𝑔 𝑝 , are found as follows: where 𝑏∈[0,1) is a user-set value modeling the amount of light emitted by a turned-off projector pixel.
𝐿 𝑝 + = max 0<𝑖≤𝑘 𝐼 𝑖 𝑝 ,
𝐿 𝑝 − = min 0<𝑖≤𝑘 𝐼 𝑖 𝑝 ,
𝐿 𝑑 𝑝 = 𝐿 𝑝 + − 𝐿 𝑝 − 1−𝑏 ,
𝐿 𝑔 𝑝 =2 𝐿 𝑝 − − 𝑏𝐿 𝑝 + 1− 𝑏 2 ,

8. Reconstruction Triangulation Line-Plane Intersection
Line-Line Intersection
Triangulation by line-plane intersection↑
Triangulation by line-line intersection↑

9. Point cloud of reconstruction result ↑
Capturing picture↑
Point cloud of reconstruction result ↑

10. Conclusion A new method to simply calibrate projector-camera system.
Robust the capturing image with adaptive threshold.
More accurate reconstruction result.

11. Thank for your listening.