Sergey A. Sukhanov, "3D content production"
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Transcript of Sergey A. Sukhanov, "3D content production"
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Sukhanov S. 3D content production 1
3D content production
St. Petersburg Electrotechnical University, St. Petersburg, Russia
Sergey A. Sukhanov
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Sukhanov S. 3D content production 2
Outline
1.What is 3D
2.3D Technology
3.The need for 3D video content
4.Live camera capture
5.2D to 3D conversion
6.Depth maps and depth image
based rendering (DIBR) method
7.Conclusion
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Sukhanov S. 3D content production 3
What is 3D?
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Sukhanov S. 3D content production 4
3D Technology
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Sukhanov S. 3D content production 5
3D Content Production
Three main approaches to creating 3-D content:
• live camera capture
• computer generated imagery (CGI)
• 2D to 3D conversion
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Sukhanov S. 3D content production 6
Live camera captureLive camera capture: recording stereo sequences of images simultaneously
A depth-range camera Special 3D cameras (single body)
Special 3D cameras (single body)side-by-side rig
side-by-side rig
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Sukhanov S. 3D content production 7
Depth map
Regular 2D color videoAccompanying 8-bit depth-images with the
same spatio-temporal resolution
The depth-images are normalized to a near clipping plane Znear and a far clipping plane Zfar.
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Sukhanov S. 3D content production 8
2D to 3D conversion2D to 3D conversion: using monocular depth cues obtained froma 2D sequence to generate the equivalent 3D sequence
1. Cutting out pieces of the image and nudging
them around
2. Projecting an image on a 3D model
3. Turning motion parallax into stereoscopy
4. Using depth maps and DIBR process
- challenging task because of automatic segmentation
- main purpose: to generate additional views
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Sukhanov S. 3D content production 9
Depth maps and depth image based rendering (DIBR)
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Sukhanov S. 3D content production 10
Depth maps generation
Block-matching based motion estimation4x4 block
Using previous frame as reference
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Depth maps generation
- identifies the chromatic homogeneous regions- group together pixels basing on their likeness
Color Segmentation
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Depth maps generationFusion
- to enhance the block-based depth map- to eliminate the staircase effort- to assign better depth values in each region
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Sukhanov S. 3D content production 13
Depth image based rendering
Camera configuration for generation of virtual stereoscopic images.
3D Image Warping
- projects each pixel of the real view into the 3D world- re-project these pixels back to 2D image of the virtual view
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Hole-Filling
Depth image based rendering
- occlusion: two different pixels of thereal view image are warped to the same location in the virtualview- disocclusion: is due tothe occluded area in the real view may become visible in thevirtual view
Left-eye view image created by 3D image warping with holesdue to disocculsion
Enlarged left-eye view image with stripe distortion after linearinterpolation based hole-filling
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Sukhanov S. 3D content production 15
Conclusion
Rising demand on new 3D content
• live camera capture
• 2D to 3D conversion
Advantages of proposed method:- Automation- use of a single view of the scene- effectiveness
Drawbacks:- high computational requirement- not suitable for real-time applications
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Sukhanov S. 3D content production 16
Thank you for your attention!