1. Computer Graphics II University of Illinois at Chicago Volume Rendering Presentation for Computer Graphics II Prof. Andy Johnson By Raj Vikram Singh

2. Computer Graphics II University of Illinois at Chicago Motivation Why is it different from texture based modeling techniques. Why is it different from texture based modeling techniques. VR VR Games Games CAD/CAM CAD/CAM 2D is only skin deep 2D is only skin deep

3. Computer Graphics II University of Illinois at Chicago Motivation (contd.) Application Areas Application Areas Medicine Medicine Earth Science Earth Science Biology Biology Simulations Simulations Fluid-dynamics Fluid-dynamics Structural physics Structural physics Super-realistic games of the future ?? Super-realistic games of the future ??

4. Computer Graphics II University of Illinois at Chicago Rendering Conversion from voxel space to image space Conversion from voxel space to image space Input is typically a structured grid (3D array) Input is typically a structured grid (3D array) Techniques Techniques DVR (Direct Volume Rendering) DVR (Direct Volume Rendering) 3D hardware allows geometry based rendering 3D hardware allows geometry based rendering

5. Computer Graphics II University of Illinois at Chicago Image-order rendering Ray casting (or Ray-tracing) Ray casting (or Ray-tracing) Taking camera parameters into consideration, shoot rays into the volume. Taking camera parameters into consideration, shoot rays into the volume. Use ray function to determine the final value of the pixel Use ray function to determine the final value of the pixel Do this for every pixel in the final image. Do this for every pixel in the final image.

6. Computer Graphics II University of Illinois at Chicago Image-order rendering (contd.) Ray function determines the quality of end-result Ray function determines the quality of end-result Maximum value Maximum value Average value Average value Distance to value Distance to value Compositing Compositing

7. Computer Graphics II University of Illinois at Chicago Alpha Compositing Transparency of an object is given by its alpha value Transparency of an object is given by its alpha value A 0.3 alpha value means that the object is 30 % opaque A 0.3 alpha value means that the object is 30 % opaque Typically would need the application of a transfer function beforehand Typically would need the application of a transfer function beforehand Do ray-traversal till the alpha value becomes 1 Do ray-traversal till the alpha value becomes 1 Ray

8. Computer Graphics II University of Illinois at Chicago Alpha compositing (contd.) Resample the scalar field at discrete locations along the viewing ray: Ray T(s) Back-to-front Compositing with

9. Computer Graphics II University of Illinois at Chicago Problems with ray traversal Choose step size carefully Choose step size carefully Too small and it requires too much computation Too small and it requires too much computation Too big and you miss important features Too big and you miss important features Trade off between speed and accuracy Trade off between speed and accuracy Step size = 2.0Step size = 1.0Step size = 0.1

10. Computer Graphics II University of Illinois at Chicago Problems with ray traversal (contd.) Uniform samplingVoxel by voxel traversal 3D scan conversion techniques used to create ray-traversal templates Speed vs. accuracy.

11. Computer Graphics II University of Illinois at Chicago Problems with ray traversal (contd.) With discrete sampling, its possible to miss voxels Final image will not be accurate One way is to ray-cast from the base plane and then apply perspective correction.

12. Computer Graphics II University of Illinois at Chicago Object order volume rendering Generally supported by 3D hardware Generally supported by 3D hardware Voxels are traversed from back to front and for every slice, its projection on the view plane is determined. Voxels are traversed from back to front and for every slice, its projection on the view plane is determined. Back to front ordering does not need storage for alpha bits Back to front ordering does not need storage for alpha bits

13. Computer Graphics II University of Illinois at Chicago Texture based volume rendering Supported by commodity 3D graphics cards Supported by commodity 3D graphics cards Have to download volume to the graphics card’s memory Have to download volume to the graphics card’s memory

14. Computer Graphics II University of Illinois at Chicago Texture based VR (contd.) Axis aligned slices Need good bi–linear interpolation techniques Need good bi–linear interpolation techniques Holds 3 copies of the data in memory Holds 3 copies of the data in memory View-port aligned slices Constant sampling rate Constant sampling rate

15. Computer Graphics II University of Illinois at Chicago GPU Bus  Dataset is too large to fit into local video memory Subdivide the data into Smaller chunks (bricks) Bottleneck: Bus-Bandwidth  Bad load balancing for GPU and Bus Load Brick Draw Time Bricking

16. Computer Graphics II University of Illinois at Chicago The Challenge A 1024x1024x1024 at 4 Bpv is 4 gigabytes. ( Ouch !! ) A 1024x1024x1024 at 4 Bpv is 4 gigabytes. ( Ouch !! ) DVR is based on ray- casting and is slow DVR is based on ray- casting and is slow 3D graphics cards have severe limitations on graphics memory (≤ 256 MB) 3D graphics cards have severe limitations on graphics memory (≤ 256 MB) SGIs are too expensive and dead SGIs are too expensive and dead

17. Computer Graphics II University of Illinois at Chicago Supercomputing to the rescue ? Software rendering is the only immediate practical approach Software rendering is the only immediate practical approach A dense 1 giga-voxel volume takes approximately 10-12 seconds to render on a 32 processor Pentium Xeon cluster. A dense 1 giga-voxel volume takes approximately 10-12 seconds to render on a 32 processor Pentium Xeon cluster. Rendering practical volumes in real-time at interactive rates is still far off. Rendering practical volumes in real-time at interactive rates is still far off.

18. Computer Graphics II University of Illinois at Chicago Cluster / Distributed computing Sort-first rendering Sort-first rendering Sort-last rendering Sort-last rendering

19. Computer Graphics II University of Illinois at Chicago Sort last redering Volume data is split equally amongst rendering nodes Volume data is split equally amongst rendering nodes Final step requires a more intelligent compositing of the resultant image Final step requires a more intelligent compositing of the resultant image Depth compositing ? Depth compositing ?

20. Computer Graphics II University of Illinois at Chicago Sort-first rendering Final image generation is split among participating nodes. Final image generation is split among participating nodes. Corresponding volume data is distributed accordingly Corresponding volume data is distributed accordingly E.g. Chromium E.g. Chromium

21. Computer Graphics II University of Illinois at Chicago QUESTIONS ??