1. 2D to 3D Conversion Using 3D Database For Football Scenes Kiana Calagari Final Project of CMPT880 July 2013

2. Why 2D to 3D? 3D-TVs are available, but…3D-TVs are available, but…  It takes time for enough 3D videos to be produced  Generating 3D content is so time consuming and needs expensive equipment  There is a large library of current 2D videos

3. Using 3D Database 2D Query : 3D Dataset : ?

4. How? 5 Nearest Neighbours Using HOG descriptors

5. How? Warping Using SIFT-flow

6. How? Initial Depth Map Median of the Candidates

7. How? Cross Bilateral Filtering Smoothing, While preserving the edges

8. Final Result

9. Results

10. My New Idea Instead of estimating the depth itself from the dataset... Estimate its orientation and depth gradients ! Since we’re finding similar images based on gradients

11. References J. Konrad, G. Brown, M. Wang, P. Ishwar, C. Wu and D. Mukherjee, “Automatic 2D-to-3D image conversion using 3D examples from the Internet”, Proc. SPIE Stereoscopic Displays and Applications, vol. 8288, pp.1, 2012 J. Konrad, M. Wang and P. Ishwar, “2d-to-3d image conversion by learning depth from examples”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp 16-22, 2012, IEEE K. Karsch, C. Liu and S.B. Kang, “Depth extraction from video using non-parametric sampling”, Computer Vision-- ECCV 2012, pp 775-788, 2012, Springer C. Liu, J. Yuen and A. Torralba, “Sift flow: Dense correspondence across scenes and its applications”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, no.5, pp978-994, 2011, IEEE