2d to 3d conversion using 3d database for football scenes
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2D to 3D Conversion Using 3D Database For Football Scenes. Kiana Calagari Final Project of CMPT880 July 2013. Why 2D to 3D?. 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

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2D to 3D Conversion Using 3D Database For Football Scenes

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2d to 3d conversion using 3d database for football scenes

2D to 3D ConversionUsing 3D DatabaseFor Football Scenes

KianaCalagari

Final Project of CMPT880

July 2013


Why 2d to 3d

Why 2D to 3D?

  • 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


Using 3d database

Using 3D Database

3D Dataset :

?

2D Query :


2d to 3d conversion using 3d database for football scenes

How?

  • 5 Nearest Neighbours

    Using HOG descriptors


2d to 3d conversion using 3d database for football scenes

How?

  • Warping Using SIFT-flow


2d to 3d conversion using 3d database for football scenes

How?

  • Initial Depth Map

    Median of the Candidates


2d to 3d conversion using 3d database for football scenes

How?

  • Cross Bilateral Filtering

    Smoothing, While preserving the edges


Final result

Final Result


Results

Results


My new idea

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


References

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


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