SlideShare a Scribd company logo
1 of 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

More Related Content

What's hot

Editing in TV Drama
Editing in TV DramaEditing in TV Drama
Editing in TV DramaZoe Lorenz
 
Medical image processing studies
Medical image processing studiesMedical image processing studies
Medical image processing studiesBằng Nguyễn Kim
 
Image classification using cnn
Image classification using cnnImage classification using cnn
Image classification using cnnSumeraHangi
 
deep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumordeep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumorVenkat Projects
 
Single image haze removal
Single image haze removalSingle image haze removal
Single image haze removalMohsinGhazi2
 
產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉
產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉
產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉CHENHuiMei
 
Pose estimation from RGB images by deep learning
Pose estimation from RGB images by deep learningPose estimation from RGB images by deep learning
Pose estimation from RGB images by deep learningYu Huang
 
Motivation for image fusion
Motivation for image fusionMotivation for image fusion
Motivation for image fusionVIVEKANAND BONAL
 
Editing - AS Media Studies
Editing  - AS Media StudiesEditing  - AS Media Studies
Editing - AS Media StudiesLiz Davies
 
Extended reality
Extended realityExtended reality
Extended realityNetcetera
 
Automatic left ventricle segmentation
Automatic left ventricle segmentationAutomatic left ventricle segmentation
Automatic left ventricle segmentationahmad abdelhafeez
 
Tutorial 1 - Basics of Digital Photography
Tutorial 1 - Basics of Digital PhotographyTutorial 1 - Basics of Digital Photography
Tutorial 1 - Basics of Digital PhotographyFahad Golra
 
História da fotografia
História da fotografiaHistória da fotografia
História da fotografiaMINAJOCA2010
 

What's hot (20)

Editing in TV Drama
Editing in TV DramaEditing in TV Drama
Editing in TV Drama
 
Medical image processing studies
Medical image processing studiesMedical image processing studies
Medical image processing studies
 
Image classification using cnn
Image classification using cnnImage classification using cnn
Image classification using cnn
 
David fincher as auteur
David fincher as auteurDavid fincher as auteur
David fincher as auteur
 
deep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumordeep learning applications in medical image analysis brain tumor
deep learning applications in medical image analysis brain tumor
 
Types of Film narratives
Types of Film narratives Types of Film narratives
Types of Film narratives
 
Single image haze removal
Single image haze removalSingle image haze removal
Single image haze removal
 
產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉
產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉
產研融合推手-台大AOI設備研發聯盟_台大陳亮嘉
 
Pose estimation from RGB images by deep learning
Pose estimation from RGB images by deep learningPose estimation from RGB images by deep learning
Pose estimation from RGB images by deep learning
 
Motivation for image fusion
Motivation for image fusionMotivation for image fusion
Motivation for image fusion
 
Editing - AS Media Studies
Editing  - AS Media StudiesEditing  - AS Media Studies
Editing - AS Media Studies
 
Extended reality
Extended realityExtended reality
Extended reality
 
Coco dataset
Coco datasetCoco dataset
Coco dataset
 
Video Processing Applications
Video Processing ApplicationsVideo Processing Applications
Video Processing Applications
 
G325 A2 exemplar
G325 A2 exemplar G325 A2 exemplar
G325 A2 exemplar
 
Automatic left ventricle segmentation
Automatic left ventricle segmentationAutomatic left ventricle segmentation
Automatic left ventricle segmentation
 
Deep Learning for Computer Vision: Medical Imaging (UPC 2016)
Deep Learning for Computer Vision: Medical Imaging (UPC 2016)Deep Learning for Computer Vision: Medical Imaging (UPC 2016)
Deep Learning for Computer Vision: Medical Imaging (UPC 2016)
 
Tutorial 1 - Basics of Digital Photography
Tutorial 1 - Basics of Digital PhotographyTutorial 1 - Basics of Digital Photography
Tutorial 1 - Basics of Digital Photography
 
Deep Learning for Video: Action Recognition (UPC 2018)
Deep Learning for Video: Action Recognition (UPC 2018)Deep Learning for Video: Action Recognition (UPC 2018)
Deep Learning for Video: Action Recognition (UPC 2018)
 
História da fotografia
História da fotografiaHistória da fotografia
História da fotografia
 

Similar to 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
 

Similar to 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
 

More from 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
 

More from 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
 

Recently uploaded

SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESSALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESmohitsingh558521
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxBkGupta21
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embeddingZilliz
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxLoriGlavin3
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demoHarshalMandlekar2
 
What is Artificial Intelligence?????????
What is Artificial Intelligence?????????What is Artificial Intelligence?????????
What is Artificial Intelligence?????????blackmambaettijean
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 

Recently uploaded (20)

SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESSALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptx
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embedding
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demo
 
What is Artificial Intelligence?????????
What is Artificial Intelligence?????????What is Artificial Intelligence?????????
What is Artificial Intelligence?????????
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 

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

Editor's Notes

  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.