SlideShare uma empresa Scribd logo
1 de 63
Camera Culture Ramesh  Raskar Camera Culture Associate Professor, MIT Media Lab http://raskar.info
[object Object],Ramesh  Raskar  http://raskar.info
Can you look around a corner ?
Can you decode a 5 micron feature from 3 meters away  with an ordinary camera ?
Beyond Multi-touch: Mobile 3D Interfaces?
6D Display Light sensitive 4D display One Pixel of a 6D Display = 4D Display Raskar, Saakes, Fuchs, Siedel, Lensch, 2008
 
[object Object],[object Object],[object Object],[object Object],[object Object],Course: Next Billion Cameras Wedn at 3:30pm
Looking around a corner via Transient Imaging Coded Aperture Post-capture Focus Control Bokode: Long Distance Barcode Camera Culture Group, MIT Media Lab  Ramesh  Raskar  http://raskar.info BiDi Screen Theory of Light Propagation Light Field Augmented Light Field WDF
Cameras and their Impact ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
New Topics in Camera Research ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
International Conference on  Computational Photography Papers due  November 2, 2009 http://cameraculture.media.mit.edu/iccp10
 
Traditional  Photography Lens Detector Pixels Image Mimics Human Eye for a Single Snapshot : Single View, Single Instant, Fixed  Dynamic range and Depth of field  for given Illumination in a Static  world Courtesy: Shree Nayar
Computational Photography Computational Illumination Computational Camera Scene :  8D Ray Modulator Display Generalized Sensor Generalized Optics Processing 4D Ray Bender Upto 4D  Ray Sampler Ray  Reconstruction Generalized Optics Recreate 4D Lightfield Light Sources Modulators 4D Incident Lighting 4D Light Field
Computational Photography  [Raskar and Tumblin] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Digital Epsilon Coded Essence Goal and Experience Low Level Mid Level High Level Hyper realism Raw Angle, spectrum aware Non-visual Data, GPS Metadata Priors Comprehensive Computational Photography aims to make progress on both axis Camera Array HDR, FoV Focal stack Decomposition problems Depth Spectrum LightFields Human Stereo Vision 8D reflectance field Dylan’s bicycle Transient Imaging Virtual Object Insertion Relighting Augmented Human Experience Material editing from single photo Scene completion from photos Motion Magnification
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multi-flash Camera for  Detecting Depth Edges
Depth  Edges Left Top Right Bottom Depth Edges Canny Edges
Flutter Shutter Camera Raskar, Agrawal, Tumblin [Siggraph2006] LCD opacity switched  in coded sequence
Traditional Coded Exposure Image of Static Object Deblurred Image Deblurred Image
Can you look around a corner ?
Can you look around a corner ? Kirmani, Hutchinson, Davis, Raskar 2009 Accepted for ICCV’2009,  Oct 2009 in Kyoto Impulse Response of a Scene
Femtosecond Laser as Light Source Pico-second detector array as Camera
Coded Aperture Camera The aperture of a 100 mm lens is modified Rest of the camera is unmodified Insert a  coded mask  with chosen binary pattern
In Focus Photo LED
Out of Focus Photo: Open Aperture
Out of Focus Photo: Coded Aperture
Captured Blurred Photo
Refocused on Person
Bokode: ankit mohan, grace woo, shinsaku hiura, quinn smithwick, ramesh raskar camera culture group, MIT media lab imperceptible visual tags for camera based interaction from a distance
Barcodes markers  that assist machines in understanding the real world
[object Object],[object Object],Computational Probes:  Long Distance Bar-codes Mohan, Woo,Smithwick, Hiura, Raskar Accepted as Siggraph 2009 paper
Bokode
Defocus blur of Bokode
Image greatly magnified. Simplified Ray Diagram
Our Prototypes
street-view tagging
tabletop/surface interaction
multi-user interaction
Varying Exposure Video Amit Agrawal  MERL , Yi Xu  Purdue , Ramesh Raskar,  MIT
Deblurred Result Blurred Photo
Varying Exposure Video DFT Exposure Time Exposure Time Exposure Time
Can we deal with particle-wave duality of light with modern Lightfield theory ? Young’s Double Slit Expt first null  (OPD = λ/2) Diffraction and Interferences modeled using Ray representation
Light Fields ,[object Object],[object Object],[object Object],[object Object],Goal: Representing propagation, interaction and image formation of light using  purely position and angle parameters Reference plane position direction
Light Fields for Wave Optics Effects Wigner Distribution Function Light Field LF < WDF Lacks phase properties Ignores diffraction, phase masks Radiance = Positive ALF ~ WDF Supports coherent/incoherent Radiance = Positive/Negative Virtual light sources Light Field Augmented Light Field WDF
Limitations of Traditional Lightfields Wigner Distribution Function Traditional Light Field ray optics based simple and powerful rigorous but cumbersome wave optics based limited in diffraction & interference holograms beam shaping rotational PSF
Example: New Representations Augmented Lightfields Wigner Distribution Function Traditional Light Field WDF Traditional Light Field Augmented LF Interference & Diffraction Interaction w/ optical elements ray optics based simple and powerful limited in diffraction & interference rigorous but cumbersome wave optics based Non-paraxial propagation http://raskar.scripts.mit.edu/~raskar/lightfields/
(ii) Augmented Light Field with LF Transformer WDF Light Field Augmented LF Interaction at the optical elements Augmenting Light Field to Model Wave Optics Effects , [Oh, Barbastathis, Raskar] LF propagation (diffractive) optical element LF LF LF LF LF propagation light field transformer negative radiance
Virtual light projector with real valued (possibly  negative  radiance) along a ray real projector real projector first null  (OPD = λ/2) virtual light projector
(ii) ALF with LF Transformer
Converting LCD Screen = large Camera for 3D Interactive HCI and Video Conferencing Matthew Hirsch, Henry Holtzman Doug Lanman, Ramesh Raskar BiDi Screen *
Light Sensing Pixels in LCD Display with embedded optical sensors Sharp Microelectronics Optical Multi-touch Prototype
Beyond Multi-touch: Hover Interaction ,[object Object],[object Object]
Beyond Multi-touch: Mobile Laptops Mobile
Design Vision Object Collocated Capture and Display Bare Sensor Spatial Light Modulator
Touch + Hover using Depth Sensing LCD Sensor
Overview: Sensing Depth from    Array of Virtual Cameras in LCD
Design Overview Display with embedded optical sensors LCD   ,  displaying   mask Optical sensor array ~2.5 cm ~50 cm
International Conference on  Computational Photography Papers due  November 2, 2009 http://cameraculture.media.mit.edu/iccp10
 
Looking around a corner via Transient Imaging Coded Aperture Post-capture Focus Control Bokode: Long Distance Barcode Camera Culture Group, MIT Media Lab  Ramesh  Raskar  http://raskar.info BiDi Screen Theory of Light Propagation Light Field Augmented Light Field WDF

Mais conteúdo relacionado

Mais procurados

Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...
Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...
Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...CubiCasa
 
Image super-resolution via iterative refinement.pptx
Image super-resolution via iterative refinement.pptxImage super-resolution via iterative refinement.pptx
Image super-resolution via iterative refinement.pptxxiaoyiWang32
 
Variational Autoencoders For Image Generation
Variational Autoencoders For Image GenerationVariational Autoencoders For Image Generation
Variational Autoencoders For Image GenerationJason Anderson
 
[SIGGRAPH 2016] Automatic Image Colorization
[SIGGRAPH 2016] Automatic Image Colorization[SIGGRAPH 2016] Automatic Image Colorization
[SIGGRAPH 2016] Automatic Image ColorizationSatoshi Iizuka
 
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis taeseon ryu
 
Portable Multispectral Fundus Camera
Portable Multispectral Fundus CameraPortable Multispectral Fundus Camera
Portable Multispectral Fundus CameraPetteriTeikariPhD
 
Transformer in Computer Vision
Transformer in Computer VisionTransformer in Computer Vision
Transformer in Computer VisionDongmin Choi
 
Faster R-CNN - PR012
Faster R-CNN - PR012Faster R-CNN - PR012
Faster R-CNN - PR012Jinwon Lee
 
Image processing7 frequencyfiltering
Image processing7 frequencyfilteringImage processing7 frequencyfiltering
Image processing7 frequencyfilteringshabanam tamboli
 
Variational Autoencoder
Variational AutoencoderVariational Autoencoder
Variational AutoencoderMark Chang
 
Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...
Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...
Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...BMS Institute of Technology and Management
 
Structure and Motion - 3D Reconstruction of Cameras and Structure
Structure and Motion - 3D Reconstruction of Cameras and StructureStructure and Motion - 3D Reconstruction of Cameras and Structure
Structure and Motion - 3D Reconstruction of Cameras and StructureGiovanni Murru
 
Machine Learning - Object Detection and Classification
Machine Learning - Object Detection and ClassificationMachine Learning - Object Detection and Classification
Machine Learning - Object Detection and ClassificationVikas Jain
 
image compresson
image compressonimage compresson
image compressonAjay Kumar
 
Faster R-CNN: Towards real-time object detection with region proposal network...
Faster R-CNN: Towards real-time object detection with region proposal network...Faster R-CNN: Towards real-time object detection with region proposal network...
Faster R-CNN: Towards real-time object detection with region proposal network...Universitat Politècnica de Catalunya
 
Chapter 1 introduction (Image Processing)
Chapter 1 introduction (Image Processing)Chapter 1 introduction (Image Processing)
Chapter 1 introduction (Image Processing)Varun Ojha
 
Frequency domain methods
Frequency domain methods Frequency domain methods
Frequency domain methods thanhhoang2012
 

Mais procurados (20)

Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...
Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...
Indoor Point Cloud Processing - Deep learning for semantic segmentation of in...
 
Image super-resolution via iterative refinement.pptx
Image super-resolution via iterative refinement.pptxImage super-resolution via iterative refinement.pptx
Image super-resolution via iterative refinement.pptx
 
Variational Autoencoders For Image Generation
Variational Autoencoders For Image GenerationVariational Autoencoders For Image Generation
Variational Autoencoders For Image Generation
 
[SIGGRAPH 2016] Automatic Image Colorization
[SIGGRAPH 2016] Automatic Image Colorization[SIGGRAPH 2016] Automatic Image Colorization
[SIGGRAPH 2016] Automatic Image Colorization
 
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
 
Portable Multispectral Fundus Camera
Portable Multispectral Fundus CameraPortable Multispectral Fundus Camera
Portable Multispectral Fundus Camera
 
Transformer in Computer Vision
Transformer in Computer VisionTransformer in Computer Vision
Transformer in Computer Vision
 
Image denoising
Image denoisingImage denoising
Image denoising
 
Faster R-CNN - PR012
Faster R-CNN - PR012Faster R-CNN - PR012
Faster R-CNN - PR012
 
Image processing7 frequencyfiltering
Image processing7 frequencyfilteringImage processing7 frequencyfiltering
Image processing7 frequencyfiltering
 
Variational Autoencoder
Variational AutoencoderVariational Autoencoder
Variational Autoencoder
 
Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...
Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...
Ph.D Dissertation Defense Slides on Efficient VLSI Architectures for Image En...
 
Image segmentation
Image segmentation Image segmentation
Image segmentation
 
Structure and Motion - 3D Reconstruction of Cameras and Structure
Structure and Motion - 3D Reconstruction of Cameras and StructureStructure and Motion - 3D Reconstruction of Cameras and Structure
Structure and Motion - 3D Reconstruction of Cameras and Structure
 
Machine Learning - Object Detection and Classification
Machine Learning - Object Detection and ClassificationMachine Learning - Object Detection and Classification
Machine Learning - Object Detection and Classification
 
image compresson
image compressonimage compresson
image compresson
 
Faster R-CNN: Towards real-time object detection with region proposal network...
Faster R-CNN: Towards real-time object detection with region proposal network...Faster R-CNN: Towards real-time object detection with region proposal network...
Faster R-CNN: Towards real-time object detection with region proposal network...
 
Image Compression
Image CompressionImage Compression
Image Compression
 
Chapter 1 introduction (Image Processing)
Chapter 1 introduction (Image Processing)Chapter 1 introduction (Image Processing)
Chapter 1 introduction (Image Processing)
 
Frequency domain methods
Frequency domain methods Frequency domain methods
Frequency domain methods
 

Semelhante a MIT Camera Culture Group Update July 2009

Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...
Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...
Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...Camera Culture Group, MIT Media Lab
 
Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...
Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...
Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...PetteriTeikariPhD
 
Raskar Emtech2010 Mar Final
Raskar Emtech2010 Mar FinalRaskar Emtech2010 Mar Final
Raskar Emtech2010 Mar FinalEmTech
 
Light Field Technology
Light Field TechnologyLight Field Technology
Light Field TechnologyJeffrey Funk
 

Semelhante a MIT Camera Culture Group Update July 2009 (20)

Raskar COSI invited talk Oct 2009
Raskar COSI invited talk Oct 2009Raskar COSI invited talk Oct 2009
Raskar COSI invited talk Oct 2009
 
Raskar 6Sight Keynote Talk Nov09
Raskar 6Sight Keynote Talk Nov09Raskar 6Sight Keynote Talk Nov09
Raskar 6Sight Keynote Talk Nov09
 
Raskar Ilp Oct08 Web
Raskar Ilp Oct08 WebRaskar Ilp Oct08 Web
Raskar Ilp Oct08 Web
 
Raskar Next Billion Cameras Siggraph 2009
Raskar Next Billion Cameras Siggraph 2009Raskar Next Billion Cameras Siggraph 2009
Raskar Next Billion Cameras Siggraph 2009
 
Raskar Paris Nov08
Raskar Paris Nov08Raskar Paris Nov08
Raskar Paris Nov08
 
Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...
Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...
Raskar, Rank and Sparsity in Computational Photography and Computational Ligh...
 
Raskar Mar09 Nesosa
Raskar Mar09 NesosaRaskar Mar09 Nesosa
Raskar Mar09 Nesosa
 
02 Fall09 Lecture Sept18web
02 Fall09 Lecture Sept18web02 Fall09 Lecture Sept18web
02 Fall09 Lecture Sept18web
 
Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...
Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...
Next Gen Computational Ophthalmic Imaging for Neurodegenerative Diseases and ...
 
Raskar Graphics Interface May05
Raskar Graphics Interface May05Raskar Graphics Interface May05
Raskar Graphics Interface May05
 
Raskar Graphics Interface May05 Web
Raskar Graphics Interface May05 WebRaskar Graphics Interface May05 Web
Raskar Graphics Interface May05 Web
 
Raskar Emtech2010 Mar Final
Raskar Emtech2010 Mar FinalRaskar Emtech2010 Mar Final
Raskar Emtech2010 Mar Final
 
Raskar Emtech2010 Mar Final
Raskar Emtech2010 Mar FinalRaskar Emtech2010 Mar Final
Raskar Emtech2010 Mar Final
 
Light Field Technology
Light Field TechnologyLight Field Technology
Light Field Technology
 
Raskar Banff
Raskar BanffRaskar Banff
Raskar Banff
 
Rfig Sig04 Presentation
Rfig Sig04 PresentationRfig Sig04 Presentation
Rfig Sig04 Presentation
 
Raskar Computational Camera Fall 2009 Lecture 01
Raskar Computational Camera Fall 2009 Lecture 01Raskar Computational Camera Fall 2009 Lecture 01
Raskar Computational Camera Fall 2009 Lecture 01
 
Raskar Coded Opto Charlotte
Raskar Coded Opto CharlotteRaskar Coded Opto Charlotte
Raskar Coded Opto Charlotte
 
Raskar Keynote at Stereoscopic Display Jan 2011
Raskar Keynote at Stereoscopic Display Jan 2011Raskar Keynote at Stereoscopic Display Jan 2011
Raskar Keynote at Stereoscopic Display Jan 2011
 
Raskar Sig05 Display Panel July05
Raskar Sig05 Display Panel July05Raskar Sig05 Display Panel July05
Raskar Sig05 Display Panel July05
 

Mais de Camera Culture Group, MIT Media Lab

God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar
God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar
God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar Camera Culture Group, MIT Media Lab
 
Dont follow the rainbow: How to avoid career traps that can lead you to fail,...
Dont follow the rainbow: How to avoid career traps that can lead you to fail,...Dont follow the rainbow: How to avoid career traps that can lead you to fail,...
Dont follow the rainbow: How to avoid career traps that can lead you to fail,...Camera Culture Group, MIT Media Lab
 
Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019
Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019
Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019Camera Culture Group, MIT Media Lab
 
Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...
Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...
Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...Camera Culture Group, MIT Media Lab
 

Mais de Camera Culture Group, MIT Media Lab (20)

Raskar Sig2017 Siggraph Achievement Award Talk
Raskar Sig2017 Siggraph Achievement Award TalkRaskar Sig2017 Siggraph Achievement Award Talk
Raskar Sig2017 Siggraph Achievement Award Talk
 
Lost Decade of Computational Photography
Lost Decade of Computational PhotographyLost Decade of Computational Photography
Lost Decade of Computational Photography
 
Covid Safe Paths
Covid Safe PathsCovid Safe Paths
Covid Safe Paths
 
God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar
God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar
God’s Eye View: Will global AI empower us or destroy us? | Ramesh Raskar
 
Dont follow the rainbow: How to avoid career traps that can lead you to fail,...
Dont follow the rainbow: How to avoid career traps that can lead you to fail,...Dont follow the rainbow: How to avoid career traps that can lead you to fail,...
Dont follow the rainbow: How to avoid career traps that can lead you to fail,...
 
Raskar PhD and MS Thesis Guidance
Raskar PhD and MS Thesis GuidanceRaskar PhD and MS Thesis Guidance
Raskar PhD and MS Thesis Guidance
 
Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019
Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019
Making Invisible Visible, Ramesh Raskar Keynote at Embedded Vision 2019
 
Augmented Surgeons: AI AR for Anatome, Raskar Aria 2019
Augmented Surgeons: AI AR for Anatome, Raskar Aria 2019Augmented Surgeons: AI AR for Anatome, Raskar Aria 2019
Augmented Surgeons: AI AR for Anatome, Raskar Aria 2019
 
Geo-spatial Research: Transition from Analysis to Synthesis
Geo-spatial Research: Transition from Analysis to SynthesisGeo-spatial Research: Transition from Analysis to Synthesis
Geo-spatial Research: Transition from Analysis to Synthesis
 
Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...
Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...
Split Learning versus Federated Learning for Data Transparent ML, Camera Cult...
 
Unspoken Challenges in AR and XR
Unspoken Challenges in AR and XRUnspoken Challenges in AR and XR
Unspoken Challenges in AR and XR
 
Raskar stanfordextremecompuimagingapr2016
Raskar stanfordextremecompuimagingapr2016Raskar stanfordextremecompuimagingapr2016
Raskar stanfordextremecompuimagingapr2016
 
What is SIGGRAPH NEXT? Intro by Ramesh Raskar
What is SIGGRAPH NEXT? Intro by Ramesh RaskarWhat is SIGGRAPH NEXT? Intro by Ramesh Raskar
What is SIGGRAPH NEXT? Intro by Ramesh Raskar
 
What is Media in MIT Media Lab, Why 'Camera Culture'
What is Media in MIT Media Lab, Why 'Camera Culture'What is Media in MIT Media Lab, Why 'Camera Culture'
What is Media in MIT Media Lab, Why 'Camera Culture'
 
Raskar UIST Keynote 2015 November
Raskar UIST Keynote 2015 NovemberRaskar UIST Keynote 2015 November
Raskar UIST Keynote 2015 November
 
Multiview Imaging HW Overview
Multiview Imaging HW OverviewMultiview Imaging HW Overview
Multiview Imaging HW Overview
 
Time of Flight Cameras - Refael Whyte
Time of Flight Cameras - Refael WhyteTime of Flight Cameras - Refael Whyte
Time of Flight Cameras - Refael Whyte
 
Leap Motion Development (Rohan Puri)
Leap Motion Development (Rohan Puri)Leap Motion Development (Rohan Puri)
Leap Motion Development (Rohan Puri)
 
Compressed Sensing - Achuta Kadambi
Compressed Sensing - Achuta KadambiCompressed Sensing - Achuta Kadambi
Compressed Sensing - Achuta Kadambi
 
Coded Photography - Ramesh Raskar
Coded Photography - Ramesh RaskarCoded Photography - Ramesh Raskar
Coded Photography - Ramesh Raskar
 

Último

Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CVKhem
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 

Último (20)

Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 

MIT Camera Culture Group Update July 2009

  • 1. Camera Culture Ramesh Raskar Camera Culture Associate Professor, MIT Media Lab http://raskar.info
  • 2.
  • 3. Can you look around a corner ?
  • 4. Can you decode a 5 micron feature from 3 meters away with an ordinary camera ?
  • 5. Beyond Multi-touch: Mobile 3D Interfaces?
  • 6. 6D Display Light sensitive 4D display One Pixel of a 6D Display = 4D Display Raskar, Saakes, Fuchs, Siedel, Lensch, 2008
  • 7.  
  • 8.
  • 9. Looking around a corner via Transient Imaging Coded Aperture Post-capture Focus Control Bokode: Long Distance Barcode Camera Culture Group, MIT Media Lab Ramesh Raskar http://raskar.info BiDi Screen Theory of Light Propagation Light Field Augmented Light Field WDF
  • 10.
  • 11.
  • 12. International Conference on Computational Photography Papers due November 2, 2009 http://cameraculture.media.mit.edu/iccp10
  • 13.  
  • 14. Traditional Photography Lens Detector Pixels Image Mimics Human Eye for a Single Snapshot : Single View, Single Instant, Fixed Dynamic range and Depth of field for given Illumination in a Static world Courtesy: Shree Nayar
  • 15. Computational Photography Computational Illumination Computational Camera Scene : 8D Ray Modulator Display Generalized Sensor Generalized Optics Processing 4D Ray Bender Upto 4D Ray Sampler Ray Reconstruction Generalized Optics Recreate 4D Lightfield Light Sources Modulators 4D Incident Lighting 4D Light Field
  • 16.
  • 17. Digital Epsilon Coded Essence Goal and Experience Low Level Mid Level High Level Hyper realism Raw Angle, spectrum aware Non-visual Data, GPS Metadata Priors Comprehensive Computational Photography aims to make progress on both axis Camera Array HDR, FoV Focal stack Decomposition problems Depth Spectrum LightFields Human Stereo Vision 8D reflectance field Dylan’s bicycle Transient Imaging Virtual Object Insertion Relighting Augmented Human Experience Material editing from single photo Scene completion from photos Motion Magnification
  • 18.
  • 19. Multi-flash Camera for Detecting Depth Edges
  • 20. Depth Edges Left Top Right Bottom Depth Edges Canny Edges
  • 21. Flutter Shutter Camera Raskar, Agrawal, Tumblin [Siggraph2006] LCD opacity switched in coded sequence
  • 22. Traditional Coded Exposure Image of Static Object Deblurred Image Deblurred Image
  • 23. Can you look around a corner ?
  • 24. Can you look around a corner ? Kirmani, Hutchinson, Davis, Raskar 2009 Accepted for ICCV’2009, Oct 2009 in Kyoto Impulse Response of a Scene
  • 25. Femtosecond Laser as Light Source Pico-second detector array as Camera
  • 26. Coded Aperture Camera The aperture of a 100 mm lens is modified Rest of the camera is unmodified Insert a coded mask with chosen binary pattern
  • 28. Out of Focus Photo: Open Aperture
  • 29. Out of Focus Photo: Coded Aperture
  • 32. Bokode: ankit mohan, grace woo, shinsaku hiura, quinn smithwick, ramesh raskar camera culture group, MIT media lab imperceptible visual tags for camera based interaction from a distance
  • 33. Barcodes markers that assist machines in understanding the real world
  • 34.
  • 36. Defocus blur of Bokode
  • 37. Image greatly magnified. Simplified Ray Diagram
  • 42. Varying Exposure Video Amit Agrawal MERL , Yi Xu Purdue , Ramesh Raskar, MIT
  • 44. Varying Exposure Video DFT Exposure Time Exposure Time Exposure Time
  • 45. Can we deal with particle-wave duality of light with modern Lightfield theory ? Young’s Double Slit Expt first null (OPD = λ/2) Diffraction and Interferences modeled using Ray representation
  • 46.
  • 47. Light Fields for Wave Optics Effects Wigner Distribution Function Light Field LF < WDF Lacks phase properties Ignores diffraction, phase masks Radiance = Positive ALF ~ WDF Supports coherent/incoherent Radiance = Positive/Negative Virtual light sources Light Field Augmented Light Field WDF
  • 48. Limitations of Traditional Lightfields Wigner Distribution Function Traditional Light Field ray optics based simple and powerful rigorous but cumbersome wave optics based limited in diffraction & interference holograms beam shaping rotational PSF
  • 49. Example: New Representations Augmented Lightfields Wigner Distribution Function Traditional Light Field WDF Traditional Light Field Augmented LF Interference & Diffraction Interaction w/ optical elements ray optics based simple and powerful limited in diffraction & interference rigorous but cumbersome wave optics based Non-paraxial propagation http://raskar.scripts.mit.edu/~raskar/lightfields/
  • 50. (ii) Augmented Light Field with LF Transformer WDF Light Field Augmented LF Interaction at the optical elements Augmenting Light Field to Model Wave Optics Effects , [Oh, Barbastathis, Raskar] LF propagation (diffractive) optical element LF LF LF LF LF propagation light field transformer negative radiance
  • 51. Virtual light projector with real valued (possibly negative radiance) along a ray real projector real projector first null (OPD = λ/2) virtual light projector
  • 52. (ii) ALF with LF Transformer
  • 53. Converting LCD Screen = large Camera for 3D Interactive HCI and Video Conferencing Matthew Hirsch, Henry Holtzman Doug Lanman, Ramesh Raskar BiDi Screen *
  • 54. Light Sensing Pixels in LCD Display with embedded optical sensors Sharp Microelectronics Optical Multi-touch Prototype
  • 55.
  • 56. Beyond Multi-touch: Mobile Laptops Mobile
  • 57. Design Vision Object Collocated Capture and Display Bare Sensor Spatial Light Modulator
  • 58. Touch + Hover using Depth Sensing LCD Sensor
  • 59. Overview: Sensing Depth from Array of Virtual Cameras in LCD
  • 60. Design Overview Display with embedded optical sensors LCD , displaying mask Optical sensor array ~2.5 cm ~50 cm
  • 61. International Conference on Computational Photography Papers due November 2, 2009 http://cameraculture.media.mit.edu/iccp10
  • 62.  
  • 63. Looking around a corner via Transient Imaging Coded Aperture Post-capture Focus Control Bokode: Long Distance Barcode Camera Culture Group, MIT Media Lab Ramesh Raskar http://raskar.info BiDi Screen Theory of Light Propagation Light Field Augmented Light Field WDF

Notas do Editor

  1. Since we are adapting LCD technology we can fit a BiDi screen into laptops and mobile devices.
  2. 4 blocks : light, optics, sensors, processing, (display: light sensitive display)
  3. Inference and perception are important. Intent and goal of the photo is important. The same way camera put photorealistic art out of business, maybe this new artform will put the traditional camera out of business. Because we wont really care about a photo, merely a recording of light but a form that captures meaningful subset of the visual experience. Multiperspective photos. Photosynth is an example.
  4. Comparisons
  5. Reversibly encode all the information in this otherwise blurred photo
  6. The glint out of focus shows the unusual pattern.
  7. put two projectors, one virtual projector at the middle, along this line, connecting the virtual light source, always destructive interference, does it make sense and right?
  8. in wave optics, WDF exhibit similar property, compare the two,
  9. the motivation, to augment lf, model diffraction in light field formulation
  10. put two projectors, one virtual projector at the middle, along this line, connecting the virtual light source, always destructive interference, does it make sense and right?
  11. Recall that one of our inspirations was this new class of optical multi-touch device. At the top you can see a prototype that Sharp Microelectronics has published. These devices are basically arrays of naked phototransistors. Like a document scanner, they are able to capture a sharp image of objects in contact with the surface of the screen. But as objects move away from the screen, without any focusing optics, the images captured this device are blurred.
  12. This device would of course support multi-touch on-screen interaction, but because it can measure the distance to objects in the scene a user’s hands can be tracked in a volume in front of the screen, without gloves or other fiducials.
  13. Since we are adapting LCD technology we can fit a BiDi screen into laptops and mobile devices.
  14. Thus the ideal BiDi screen consists of a normal LCD panel separated by a small distance from a bare sensor array. This format creates a single device that spatially collocates a display and capture surface.
  15. So here is a preview of our quantitative results. I’ll explain this in more detail later on, but you can see we’re able to accurately distinguish the depth of a set of resolution targets. We show above a portion of portion of views form our virtual cameras, a synthetically refocused image, and the depth map derived from it.
  16. Our observation is that by moving the sensor plane a small distance from the LCD in an optical multitouch device, we enable mask-based light-field capture. We use the LCD screen to display the desired masks, multiplexing between images displayed for the user and masks displayed to create a virtual camera array. I’ll explain more about the virtual camera array in a moment, but suffice to say that once we have measurements from the array we can extract depth.