Image Based Rendering. Fast Realistic Rendering without 3D models

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Transcription:

Light Field

Modeling a desktop

Image Based Rendering Fast Realistic Rendering without 3D models

Start from Ray Tracing Rendering is about computing color along each ray

Sampling Rays

Sampling Rays by Taking Pictures

Rendering as Ray Resampling

Ray space How to parameterize the ray space How to sample and resample rays

Two Plane Parameterization

Stanford Camera Array

Very Fast Light Field Rendering

4D interpolation Light Field Rendering

Dynamic Reparameterized Light Fields

Dynamic Reparameterized Light Fields Move to desired new focal surface Create a new 4D space with new focal surface Recove ray with Reparameterization (u, v, s, t) => (u, v, f, g) F

Dynamic Reparameterized Light Fields Recover ray r Resample from ray (s, t, f, g) and (s, t, f, g) Interpolation, reconstruction with filter,, etc

Dynamic Reparameterized Light Fields Change the shape of focal surface Gives focus on 3D object rather than planes

Dynamic Reparameterized Light Fields

Dynamic Reparameterized Light Fields

Variable Apertures Also can generate variable aperture Aperture Control amount of light Control depth of fields Aperture Filter: Control how many cameras are used to resample a required ray Larger apertures produce images with narrow range of focus

Aperture Filters

Variable Apertures

Variable Apertures

Marc Levoy Stanford multi-camera array 640 480 pixels 30 fps 128 cameras synchronized timing continuous streaming flexible arrangement

Marc Levoy Ways to use large camera arrays widely spaced tightly packed intermediate spacing light field capture high-performance imaging synthetic aperture photography

Marc Levoy Intermediate camera spacing: synthetic aperture photography

Example using 45 cameras [Vaish CVPR 2004] Marc Levoy

Tiled camera array Can we match the image quality of a cinema camera? world s largest video camera no parallax for distant objects poor lenses limit image quality seamless mosaicing isn t hard

Tiled panoramic image (before geometric or color calibration)

Tiled panoramic image (after calibration and blending)

Tiled camera array Can we match the image quality of a cinema camera? world s largest video camera no parallax for distant objects poor lenses limit image quality seamless mosaicing isn t hard per-camera exposure metering HDR within and between tiles

same exposure in all cameras individually metered checkerboard of exposures

Marc Levoy High-performance photography as multi-dimensional sampling spatial resolution field of view frame rate dynamic range bits of precision depth of field focus setting color sensitivity

Light field photography using a handheld plenoptic camera Ren Ng, Marc Levoy, Mathieu Brédif, Gene Duval, Mark Horowitz and Pat Hanrahan Stanford University

Marc Levoy What s wrong with conventional cameras? Aperture

Capture the light field inside a camera Aperture 500 microns 125*125 μm Marc Levoy

Marc Levoy Conventional versus light field camera uv-plane st-plane

Marc Levoy Conventional versus light field camera st-plane uv-plane

Prototype camera Contax medium format camera Kodak 16-megapixel sensor Adaptive Optics microlens array 125μ square-sided microlenses 4000 4000 pixels 292 292 lenses = 14 14 pixels per lens

Light Field in a Single Exposure Marc Levoy

Light Field in a Single Exposure Marc Levoy

Light field inside a camera body Marc Levoy

Marc Levoy Digitally stopping-down Σ Σ stopping down = summing only the central portion of each microlens

Marc Levoy Digital refocusing Σ Σ refocusing = summing windows extracted from several microlenses

Example of digital refocusing Marc Levoy

Refocusing portraits Marc Levoy

Action photography Marc Levoy

Extending the depth of field conventional photograph, main lens at f / 4 conventional photograph, main lens at f / 22

Marc Levoy Scene-dependent focal plane Σ Depth from focus problem Interactive solution [Agarwala 2004]

Extending the depth of field conventional photograph, main lens at f / 4 conventional photograph, main lens at f / 22 light field, main lens at f / 4, after all-focus algorithm [Agarwala 2004] Marc Levoy

Marc Levoy A digital refocusing theorem an f / N light field camera, with P P pixels under each microlens, can produce views as sharp as an f / (N P) conventional camera these views can be focused anywhere within the depth of field of the f / (N P) camera

Marc Levoy Prior work integral photography microlens array + film application is autostereoscopic effect [Adelson 1992] proposed this camera built an optical bench prototype using relay lenses application was stereo vision, not photography

Marc Levoy Digitally moving the observer Σ moving the observer = moving the window we extract from the microlenses Σ

Example of moving the observer Marc Levoy

Moving backward and forward Marc Levoy

Marc Levoy Implications cuts the unwanted link between exposure (due to the aperture) and depth of field trades off (excess) spatial resolution for ability to refocus and adjust the perspective sensor pixels should be made even smaller, subject to the diffraction limit 36mm 24mm 2.5μ pixels = 266 megapixels 20K 13K pixels 4000 2666 pixels 20 20 rays per pixel Application in microscope