'Light fields' presentation slideshows

Light field photography and microscopy

530 views • 52 slides

Real-Time High Quality Rendering

Real-Time High Quality Rendering. CSE 291 [Winter 2015] , Lecture 6 Image-Based Rendering and Light Fields. http:// www.cs.ucsd.edu /~ ravir. Motivation for Lecture. IBR is tangentially related to course (more pertinent to acquisition of measured materials and scenes)

591 views • 45 slides

Advanced Computer Graphics (Spring 2013)

Advanced Computer Graphics (Spring 2013). CS 283, Lecture 15: Image-Based Rendering and Light Fields Ravi Ramamoorthi. http:// inst.eecs.berkeley.edu /~cs283 /sp13. Next few slides courtesy Paul Debevec; SIGGRAPH 99 course notes. IBR: Pros and Cons. Advantages

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Image-Based Modeling and Rendering

Image-Based Modeling and Rendering. CS 6998 Lecture 6. Next few slides courtesy Paul Debevec; SIGGRAPH 99 course notes. IBR: Pros and Cons. Advantages Easy to capture images: photorealistic by defn Simple, universal representation Often bypass geometry estimation?

429 views • 42 slides

Image-Based Rendering

Image-Based Rendering. Computer Graphics. Image-Based Rendering. Image-Based Rendering is a series of techniques that all involve 2D images as the primary data rather than 3D models The main goal is to decouple rendering time from scene complexity

975 views • 41 slides

Measuring BRDFs

Measuring BRDFs. Why bother modeling BRDFs? Why not directly measure BRDFs?. True knowledge of surface properties Accurate models for graphics. Measure, measure, measure: BRDF, BTF, Light Fields. Thanks to Steve Marschner, Shree Nayar, Ravi Ramamoorthi,

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Interactive Deformation of Light Fields

Interactive Deformation of Light Fields. Billy Chen , Marc Levoy Stanford University Eyal Ofek , Heung-Yeung Shum Microsoft Research Asia. To appear in the Symposium on Interactive 3D Graphics and Games (I3D) 2005 conference proceedings. Abstract.

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CS 395/495-25: Spring 2003

CS 395/495-25: Spring 2003. IBMR: Week 10A Dimensionality of IBMR Methods Jack Tumblin jet@cs.northwestern.edu. Reminders. ProjA graded: Good Job! 90,95, 110 ProjB graded: Good! minor H confusions. MidTerm graded: novel solutions encouraged. ProjC due Friday, May 16: graded.

331 views • 33 slides

New sensors and models for complex environmental conditions

New sensors and models for complex environmental conditions. John N. Porter University of Hawaii. If one cannot accurately measure the in situ optical properties of the environment, then developing a satellite remote sensing algorithm is like trying to hit a target with poor vision

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Computational Photography and Videography

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Computational Photography and Videography

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Image-Based Rendering: 1st Wave

Image-Based Rendering: 1st Wave. Definition : Using images to enhance the realism of 3D graphics Brute Force in Image-Space, L. Williams Texture maps for surface detail Mipmapping (antialiasing) Zbuffers for hidden surfaces Shadow mattes and maps Object tags.

324 views • 19 slides

Dual Representations for Light Field Compression

Dual Representations for Light Field Compression. EE368C Project January 30, 2001 Peter Chou Prashant Ramanathan. Outline. Background Model-based Coding Surface Light Fields Trade-offs Duality Proposed Experiments. Light Fields and Compression. What are light fields?

249 views • 13 slides