1 / 17

A Novel 2D-to-3D Conversion System Using Edge Information

A Novel 2D-to-3D Conversion System Using Edge Information. IEEE Transactions on Consumer Electronics 2010 Chao-Chung Cheng Chung- Te li Liang-Gee Chen. Introduction. Some approaches that can generate 3D content Time-of-flight depth sensor Triangular stereo vision 3D graph rendering.

laban
Télécharger la présentation

A Novel 2D-to-3D Conversion System Using Edge Information

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Novel 2D-to-3D Conversion System Using Edge Information IEEE Transactions on Consumer Electronics 2010 Chao-Chung Cheng Chung-Te li Liang-Gee Chen

  2. Introduction • Some approaches that can generate 3D content • Time-of-flight depth sensor • Triangular stereo vision • 3D graph rendering

  3. Introduction • How does our brain perceive depth? • Monocular cues：one of the major categories for depth perception • Motion parallax • Binocular cues

  4. Monocular cues • Interposition (overlapping) • Relative Height • Familiar Size • Texture Gradient • Shadow • Linear Perspective

  5. Proposed System • Block-Based Region Grouping • Depth from Prior Hypothesis • 3D Image Visualization using Bilateral Filtering and Depth Image-Based Rendering

  6. Proposed 2D-to-3D Conversion System

  7. Block-Based Region Grouping • Measure the similarity of neighboring blocks • The blocks are segmented into multiple groups by MST

  8. Depth from Prior Hypothesis • Use a line detection algorithm[9] to detect the linear perspective of the scene C.-C. Cheng, C.-T. Li, P.-S. Huang, T.-K. Lin, Y.-M. Tsai, and L.-G. Chen, “A block-based 2D-to-3D conversion system with bilateral filter,” in Proc. IEEE Int. Conf. Consumer Electronics, 2009

  9. Depth from Prior Hypothesis • Find the corresponding depth map gradients • Compute the gravity center of the block group as the depth

  10. 3D Image Visualization using Bilateral Filtering and Depth Image-Based Rendering • Remove the blocky artifacts by cross bilateral filter • Then the depth map is used to generate 3D image by DIBR[3] W.-Y. Chen and Y.-L. Chang and S.-F. Lin and L.-F. Ding and L.-G. Chen, “Efficient depth image based rendering with edge dependent depth filter and interpolation,” in Proc. ICME, pp. 1314-1317, 2005

  11. Experiment Result • Analysis of Computational Complexity • Analysis of Visual Quality

  12. Analysis of Computational Complexity • The computational complexity is • Larger block size implies shorter computational time but lower depth map quality

  13. Analysis of Visual Quality

  14. Analysis of Visual Quality

  15. Analysis of Visual Quality • Comparing the depth quality and visual comfort over 4 video data types • Videos that captured by a stereoscopic camera • Proposed algorithm • Previous work of [9] • Commercial software of DDD’s TriDef

  16. Analysis of Visual Quality

  17. Conclusion • The proposed algorithm uses edge information to group the image into coherent regions. • A simple depth hypothesis is determined by the linear perspective of the scene. • The algorithm is quality-scalable depending on the block size.

More Related