volume graphics what’s in the cards…

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Volume Graphics What’s in the cards…

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Volume Graphics What’s in the cards…. The Panelists. Kwan-Liu Ma. The Panelists. Kwan-Liu Ma. Min Chen. The Panelists. Kwan-Liu Ma. Min Chen. Baoquan Chen. The Panelists. Kwan-Liu Ma. Min Chen. Baoquan Chen. Michael Meissner. The Panelists. Kwan-Liu Ma. Min Chen. Baoquan Chen. - PowerPoint PPT Presentation

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Page 1: Volume Graphics What’s in the cards…

Volume Graphics

What’s in the cards…

Page 2: Volume Graphics What’s in the cards…

The Panelists

Kwan-Liu Ma

Page 3: Volume Graphics What’s in the cards…

The Panelists

Kwan-Liu Ma Min Chen

Page 4: Volume Graphics What’s in the cards…

The Panelists

Kwan-Liu Ma Min Chen Baoquan Chen

Page 5: Volume Graphics What’s in the cards…

The Panelists

Kwan-Liu Ma Min Chen Baoquan Chen MichaelMeissner

Page 6: Volume Graphics What’s in the cards…

The Panelists

Kwan-Liu Ma Min Chen Baoquan Chen MichaelMeissner

Klaus Mueller

Page 7: Volume Graphics What’s in the cards…

The Good Cards

wideacceptance

Page 8: Volume Graphics What’s in the cards…

The Good Cards

wideacceptance

availabledata

Page 9: Volume Graphics What’s in the cards…

The Good Cards

wideacceptance

availabledata

lots ofresearch

Page 10: Volume Graphics What’s in the cards…

The Good Cards

wideacceptance

availabledata

lots ofresearch

speed(GPU)

Page 11: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 12: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 13: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 14: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 15: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 16: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 17: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 18: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 19: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 20: Volume Graphics What’s in the cards…

Ten Issues at VG99• Storage (polys vs. voxels)• Effects (reflections, refractions, shadows)• Radiosity – is it easier/better with voxels? • Potential for modeling• Can the “Visible Human” walk?• Volume test data (a teapot with actual tea)• Role of image processing and computer vision• A stack of images is a volume (modeling)• Availability of real-time volume rendering• Penetration of volume graphics into other

disciplines (think Siggraph…)

Page 21: Volume Graphics What’s in the cards…

Issues: Reality Check

• Storage (polys vs. voxels) storage (texture memory)

Page 22: Volume Graphics What’s in the cards…

Issues: Reality Check

• Storage (polys vs. voxels) storage (texture memory)

• Effects (reflections, refractions, shadows) effects (illustrative volume rendering)

Page 23: Volume Graphics What’s in the cards…

Issues: Reality Check

• Storage (polys vs. voxels) storage (texture memory)

• Effects (reflections, refractions, shadows) effects (illustrative volume rendering)

• Radiosity – is it easier/better with voxels? simulation of amorphous phenomena

Page 24: Volume Graphics What’s in the cards…

Issues: Reality Check

• Storage (polys vs. voxels) storage (texture memory)

• Effects (reflections, refractions, shadows) effects (illustrative volume rendering)

• Radiosity – is it easier/better with voxels? simulation of amorphous phenomena

• Potential for modeling deformation with haptics

Page 25: Volume Graphics What’s in the cards…

Issues: Reality Check• Storage (polys vs. voxels)

storage (texture memory)

• Effects (reflections, refractions, shadows) effects (illustrative volume rendering)

• Radiosity – is it easier/better with voxels? simulation of amorphous phenomena

• Potential for modeling deformation with haptics

• Can the “Visible Human” walk? Yes!

Page 26: Volume Graphics What’s in the cards…

courtesy of D. Silver

Page 27: Volume Graphics What’s in the cards…

Issues: Reality Check

• Volume test data (a teapot with actual tea) still not much, submit to volvis.org

Page 28: Volume Graphics What’s in the cards…

Issues: Reality Check

• Volume test data (a teapot with actual tea) still not much, submit to volvis.org

• Role of image processing and computer vision much better understanding of filters, etc.

Page 29: Volume Graphics What’s in the cards…

Issues: Reality Check

• Volume test data (a teapot with actual tea) still not much, submit to volvis.org

• Role of image processing and computer vision much better understanding of filters, etc.

• A stack of images is a volume video visualization

Page 30: Volume Graphics What’s in the cards…

Issues: Reality Check

• Volume test data (a teapot with actual tea) still not much, submit to volvis.org

• Role of image processing and computer vision much better understanding of filters, etc.

• A stack of images is a volume video visualization

• Availability of real-time volume rendering GPUs !!!

Page 31: Volume Graphics What’s in the cards…

Issues: Reality Check• Volume test data (a teapot with actual tea)

still not much, submit to volvis.org

• Role of image processing and computer vision much better understanding of filters, etc.

• A stack of images is a volume video visualization

• Availability of real-time volume rendering GPUs !!!

• Penetration of volume graphics into other disciplines (think Siggraph…)

3D textures, subsurface scattering, virtual voyage

Page 32: Volume Graphics What’s in the cards…

New Issues

• User interfaces transfer functions are a pain

• Modeling tool surface splatting vs. volume splatting

• Large datasets are still a problem multi-variate, multi-valued ones, too

• Strides in segmentation are direly needed need to get features from the scanned datasets

• Better understanding of perceptional issues how can we best accentuate the features we find

Page 33: Volume Graphics What’s in the cards…

Panelists… GO

Kwan-Liu Ma Min Chen Baoquan Chen MichaelMeissner

Page 34: Volume Graphics What’s in the cards…

Ten Issues for 2005

1. Proof of reliability and accuracy2. Make interface more simple and less daunting3. Work closely with other disciplines4. Visual data mining and analysis5. Effective visualization, not so much exploratory6. Make more popular for target groups7. Incorporation of cognition and perception8. Usability9. Make it taste like beer10. Make it taste like a lobster

Page 35: Volume Graphics What’s in the cards…

Ten Issues for 2005

1. Proof of reliability and accuracy2. Make interface more simple (create information interfaces)3. Work closely with other disciplines4. Visual data mining / analysis / feature extraction (segmentation)5. Effective / illustrative visualization, not so much exploratory6. Make more popular for target groups7. Incorporation of cognition and perception8 User study / validation / common framework for this9. Framework to integrate algorithms (VolumeShop Pro)10. Global illumination