Understanding Laser Sensor and its Calibration with Camera

1. Understanding Laser Sensorand its Calibration with Camera Youngjin Yoon / YongseopJeong Apr. 16, 2012 Robotics and Computer Vision Laboratory KAIST

2. System Configuration Camera Camera Laser Laser

3. Laser Range Finder • Device which uses a laser beam to determine the distance to objects

4. Laser Range Finder: LMS151 • Specifications • Using 905nm IR • Field of view: 270º • 50Hz Scanning Freq. • 0.5º angular resolution • Operating Range: 0~50m • Max. range with 10% reflectivity: 18m

5. Sample Laser Scanner Data Pattern Laser For Left camera, you need only left pattern

6. Objectives Camera 2 Camera 1 Laser Scanner To estimate, you should find first. [1,2] Find then estimate (optional)

7. What is Camera Calibration? • Estimating extrinsic relation between 3D world and 2D camera and the camera internal parameter 1) Intrinsic parameter K • Optical/geometrical property of a camera 2) Extrinsic Parameter [R|t] • Rotation and translation matrix

8. Camera Calibration[1] • Estimate Homography • Intrinsic parameter estimation (K) • Extrinsic parameter estimation ([R|t]) • Stereo Calibration(Optional)

9. RecommendedExperiment Schedule • Week 1, 4/16(Mon.) – 4/22(Sun.) • Camera intrinsic parameter estimation • Extrinsic parameter of Camera 1 • is defined in world coordinates • Note that each image derives each • But is unique.

10. RecommendedExperiment Schedule • Week 2, 4/23(Mon.) – 4/29(Sun.) • Extrinsic parameter of Laser • : Relative pose of the laser range finder w.r.t. the Camera 1

11. RecommendedExperiment Schedule • Extra work • and • Non-overwrapping stereo calibration • is the relative pose w.r.t. the Camera1 • You’ll receive super-extra points

12. RecommendedExperiment Schedule • You don’t have to submit 2 reports • Just submit the result of 2 weeks until the due date.

13. Given data • Pattern image • Pattern.zip • Includes pictures of patterns from camera 1 and 2 • Laser Data • Laser.zip

14. Extra Points • Compute K, R and t without toolbox • Automatic feature extraction from pattern • Get each pixel point automatically • Optimization • Non-overwrapping stereo calibration • Extra work

15. Submission • Due: 23:59:59, April 29(Sun.), 2012 • YoungjinYoon(yjyoon@rcv.kaist.ac.kr) • Title: [RE510] ID - NAME • Example: [RE510] 20113573 – Lee Myungbak • Attachment file • Report (doc, docx, hwpor pdf) • Executable File • Source Code(compile-able) • All used libraries must be included in submitted package

16. Submission: Report • Report should contain • The answers; , , , • Justify your answer with any means • Calculating re-projection error or project laser ray on image sets • Your progress to estimate them • List of used toolbox(es) and libraries • Referred resources(papers, books, etc.) • Developing Environment • Version of OS, MSVS, MATLAB, … • Don’t attach whole source code in your report! • Detailed explanation and comment on source code is enough • Language: Korean, English

17. Submission: Executable File • Remarks • Compiled(executable) file should be attached in a separate folder • With required dll, lib, data files and etc. • If you used MATLAB, m-files are OK • With a execution manual • If your program is not executable, you’ll lose a lot of points • Please check your program on another computer

18. Submission: Source Code • Remarks • PLEASE add comments • Include all libraries you used • Your project should be compiled on our computer

19. Grading Policy

20. Reference [1] Flexible Camera Calibration By Viewing a Plane From Unknown Orientations • Zhengyou Zhang, ICCV 1999 [2] Extrinsic Calibration of a Camera and Laser Range Finder(improves camera calibration) • Qilong Zhang, Robert Pless, IROS 2004 [3] Multiple View Geometry (2/E) • Hartley, Zisserman