1. Stereoscopic 3D 2013/10/30

2. Stereoscopic Image Transforms to Autostereoscopic Multiplexed Image Wei-Ming Chen, Chi-Hao Chiou and Sheng-Hao Jhang Computer Science and Automation Engineering (CSAE), 2011

3. Outline Introduction Related Work Proposed Method Experimental Results Conclusion 3

4. Introduction 4

5. 3D technologies have become popular in recent years. Widely applied to movie, films and show. In early 3D vision technology: Anaglyph Polarization Shutter 5 With special glasses

6. Anaglyph Glass

7. Polarization Glass

8. Shutter Glass

9. Introduction Autostereoscopic 3D display Non-glass system Propose a new technique for generating Autostereoscopic multiplexed content. 9 Objective:

10. Related Work 10

11. Disparity Vertical Parallax Usually = 0 focus on horizontal parallax Horizontal Parallax Identify the distance of the object

12. Disparity retina

13. Image Rectification Zero Parallax Zero parallax plane

14. Image Rectification Simplified to one dimension - horizontal

15. Solution : All epipolar lines are parallel in the rectified image plane. Image Rectification

16. 3D coordinate of real scene: Disparity to Depth f : focal length b : the length of baseline d : disparity (u 0, v 0 ) : coordinate of image center (camera intrinsic parameter matrix K) (u, v) : pixel coordinate Du Xin, Zhu Yun-fimg, "A Flexible Method for 3D Reconstruction of Urban Building", ICSP 2008 proceedings. Baseline Epipolar line

17. 3D Reconstruction Wei-wei Ma, My-Ha Le, Kang-Hyun Jo, "3D Reconstruction and Measurement of Indoor Object Using Stereo Camera", The 6th International Forum on Strategic Technology, 2011.

18. Autostereoscopic 3D display Time-multiplexed Switch rapidly (left and right images) 2D & 3D : same resolution Spatial-multiplexed Parallax barrier Lenticular lenses Lower resolution for 3D 18

19. Autostereoscopic 3D display Parallax barrier 19 Lenticular lenses

20. Proposed Method 20

21. System Flow of Depth-map Generation 21 Stereo matching

22. Depth-map Generation 1) Feature point detection Use SURF algorithm [5] (based on SIFT) 2) Epipolar Geometry Matching the feature points 3) Interpolation Estimate the pixels which is not feature points 4) Graphcut Grouping the close pixels (segmentation) 22 Disparity between stereo images [5] H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "Speeded-Up Robust Features (SURF)," Computer Vision and Image Understanding, vol. 110, pp. 346-359, 2008.

23. System Flow of Synthesis 23

24. Zero-parallax setting The most comfortably distance between user and display could be determined from Z c. Z c ( Base plane) ： 24 Z far : the highest depth map value Z near : the lowest depth map value

25. Pre-processing the Depth Map Mean filter Gaussian filter 25

26. 3D-image Warping Multi-View ： Need large storage space use depth map to create virtual views Warping ： Reference view → Virtual view 26 warp

27. 3D-image Warping Multi-View ： Need large storage space use depth map to create virtual views 27 Warping

28. 3D-image Warping Lenticular autostereoscopic display DIBR 28 S0S0 The pixel position of the center view k View ID ( K= -4 ~ 4 ) b The distance between two eyes ZFZF Farthest distance ZNZN Nearest distance pzpz Depth value Pixels/cm (according to monitor) d Distance between eyes and screen

29. Issues[*]: Disparity Range Limitations of perception and technology Disparity Sensitivity More sensitive to nearby objects Disparity Gradient Disparity Velocity Temporal information 3D-image Warping 29 [*] :Lang, M., Hornung, A., Wang, O., Poulakos, S., Smolic, A. & Gross, M. (2010, July). Nonlinear Disparity Mapping for Stereoscopic 3D. To appear in ACM Transactions on Graphics (Proc. SIGGRAPH).

30. Disoccluded Regions-filling Disoccluded Regions : regions without warped pixel 30 warp Reference view Virtual view

31. Disoccluded Regions-filling Associated with DIBR: 31 Similar to occlusion handling

32. Disoccluded Regions-filling 32

33. Experimental Results 33

34. Experimental Results Disoccluded Regions-filling: 34 Previous Work Proposed

35. Experimental Results 35 The six warping views The six warping views

36. Experimental Results 36 Synthesized result

37. Conclusion 37

38. Conclusion 3D-image generation of stereo images with good 3D effect was proposed. Future : using temporal information Stereo images → Disparity map → 3D warping → Hole filling Issues: Zero-parallax setting Disparity Range / Disparity Velocity Hole filling 38

39. Reference Optical Design, Fabrication, and Measurement 3D Introduction and Project (Dept. of Photonics & Display Institute,National Chiao Tung University) Image Rectification (Stereo), Guido Gerig AGENCY1903 BLOG http://www.agency1903.com/blog/2010/8/18/z-axis-power http://www.agency1903.com/blog/2010/8/18/z-axis-power 基於 3D 顯示器格式之即時 3D 內容合成技術 ( 劉楷哲、吳其霖、黃偉豪、陳信榮、李錕、羅豐祥 )