Automatic Projector Calibration with Embedded Light Sensors

•Transferir como PPT, PDF•

1 gostou•608 visualizações

Vertigo4

Educação

Automatic Projector Calibration with Embedded Light Sensors Ph.D. Johnny C. Lee Ph.D. Paul H. Dietz Ph.D. Dan Maynes-Aminzade Ph.D. Ramesh Raskar Ph.D. Rogerio Mallet Ph.D. Uli Dieter Carnegie Mellon University Mitsubishi Electric Research Labs Stanford University Äachen Universität Fraunhöfer Gesellschaft

Our Approach ,[object Object],[object Object],[object Object],[object Object]

Calibration Demo Demonstration of calibration process

Gray Code Patterns ,[object Object],[object Object],[object Object]

Binary Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 0111 0101 0100 1100 1101 1111 1110 1010 1011 1001 1000

Scalability and Robustness ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Angular Robustness & Mirrors Demonstration Video

Optical Path Optical path between the projector and the sensor does not need to be known. Pixel location of a sensor can be found so long as there exists a path. Additional sensors in the target surface can increase robustness to partial occlusion.

Application Demonstrations Demonstration Video

Research Applications Everywhere Displays Digital Merchandising ShaderLamps, projector AR

Other Applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Trade Offs ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Future Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Concluding remarks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

[object Object],[object Object],[object Object],Thanks! Haptic Pen: A Tactile Feedback Stylus for Touch Screens Wednesday 3pm session

Homography ,[object Object],[object Object],[object Object],[object Object],Four sensor coordinates are used to compute a homography – (loosely) a transformation between two coordinate spaces.

vs. Camera Based Approach ,[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]

Mais conteúdo relacionado

Mais procurados

D04432528IOSR-JEN

20110220 computer vision_eruhimov_lecture01Computer Science Club

SIGGRAPH 2014 Course on Computational Cameras and Displays (part 2)Matthew O'Toole

ANALYSIS OF ADAPTIVE FILTER AND ICA FOR NOISECANCELLATION FROM A VIDEO FRAMENexgen Technology

Radt 228 mod 5 ppt dig process & manipula.kmohney

RSS and Sensor Fusion Algorithms for Indoor Location Systems on SmartphonesUOC Universitat Oberta de Catalunya

Ijetcas14 479Iasir Journals

Compressed Sensing - Achuta KadambiCamera Culture Group, MIT Media Lab

SIGGRAPH 2014 Course on Computational Cameras and Displays (part 1)Matthew O'Toole

Sensors On 3d DigitizationRajan Kumar

IJRET-V1I1P2 -A Survey Paper On Single Image and Video Dehazing MethodsISAR Publications

“Person Re-Identification and Tracking at the Edge: Challenges and Techniques...Edge AI and Vision Alliance

Ijmsr 2016-10ijmsr

Rfig Sig04 PresentationCamera Culture Group, MIT Media Lab

Tobias Rothermel (pmd technologies): pmd ToF – the Swiss Army Knife of 3D Sen...AugmentedWorldExpo

Automatic Building detection for satellite Images using IGV and DSMAmit Raikar

IRJET- Photo Restoration using Multiresolution Texture Synthesis and Convolut...IRJET Journal

CORNAR: Looking Around Corners using Trillion FPS ImagingCamera Culture Group, MIT Media Lab

Compressive DIsplays: SID Keynote by Ramesh RaskarCamera Culture Group, MIT Media Lab

Mais procurados (19)

D04432528

20110220 computer vision_eruhimov_lecture01

SIGGRAPH 2014 Course on Computational Cameras and Displays (part 2)

ANALYSIS OF ADAPTIVE FILTER AND ICA FOR NOISECANCELLATION FROM A VIDEO FRAME

Radt 228 mod 5 ppt dig process & manipula.

RSS and Sensor Fusion Algorithms for Indoor Location Systems on Smartphones

Ijetcas14 479

Compressed Sensing - Achuta Kadambi

SIGGRAPH 2014 Course on Computational Cameras and Displays (part 1)

Sensors On 3d Digitization

IJRET-V1I1P2 -A Survey Paper On Single Image and Video Dehazing Methods

“Person Re-Identification and Tracking at the Edge: Challenges and Techniques...

Ijmsr 2016-10

Rfig Sig04 Presentation

Tobias Rothermel (pmd technologies): pmd ToF – the Swiss Army Knife of 3D Sen...

Automatic Building detection for satellite Images using IGV and DSM

IRJET- Photo Restoration using Multiresolution Texture Synthesis and Convolut...

CORNAR: Looking Around Corners using Trillion FPS Imaging

Compressive DIsplays: SID Keynote by Ramesh Raskar

Semelhante a Automatic Projector Calibration with Embedded Light Sensors

Digital Detectors for Industrial Applications-Nityanand GopalikaNityanand Gopalika

Brochure s neoxsm_carvalho

“Building the Eyes of a Vision System: From Photons to Bits,” a Presentation ...Edge AI and Vision Alliance

Temporal Contrast Vision SensorNisarg Shah

Rfid based localizationMehjabin Sultana

Ee 417 Senior Designcrouchj1

Advanced Sensor Tech : SpectRx™ , Lightning Speed & Hardness Test Game ChangerSabrie Soloman

Computer Vision for Measurement & FRRekaNext Capital

2013 Lecture3: AR Tracking Mark Billinghurst

Defying Nyquist in Analog to Digital ConversionDistinguished Lecturer Series - Leon The Mathematician

Digital Image Correlation Presentationtrilionqualitysystems

Dataset creation for Deep Learning-based Geometric Computer Vision problemsPetteriTeikariPhD

Dr,system abhishekDrAbhishek Gowda

Rate and Performance Analysis of Indoor Optical Camera Communications in Opti...Willy Anugrah Cahyadi

Kinect for Windows SDK - Programming GuideKatsuhito Okada

Innovate in new and exciting optical sensing applications in industrial marke...Design World

Khaled Sarayeddine (Optinvent): Optical Technologies & Challenges for Next Ge...AugmentedWorldExpo

Dip lect2-Machine Vision Fundamentals Abdul Abbasi

Digital ImagingDipika Bumb, Indian Cancer Society, New Delhi

TechSheet_Focus3D X 330Derrick McBreairty

Semelhante a Automatic Projector Calibration with Embedded Light Sensors (20)

Digital Detectors for Industrial Applications-Nityanand Gopalika

Brochure s neox

“Building the Eyes of a Vision System: From Photons to Bits,” a Presentation ...

Temporal Contrast Vision Sensor

Rfid based localization

Ee 417 Senior Design

Advanced Sensor Tech : SpectRx™ , Lightning Speed & Hardness Test Game Changer

Computer Vision for Measurement & FR

2013 Lecture3: AR Tracking

Defying Nyquist in Analog to Digital Conversion

Digital Image Correlation Presentation

Dataset creation for Deep Learning-based Geometric Computer Vision problems

Dr,system abhishek

Rate and Performance Analysis of Indoor Optical Camera Communications in Opti...

Kinect for Windows SDK - Programming Guide

Innovate in new and exciting optical sensing applications in industrial marke...

Khaled Sarayeddine (Optinvent): Optical Technologies & Challenges for Next Ge...

Dip lect2-Machine Vision Fundamentals

Digital Imaging

TechSheet_Focus3D X 330

Último

Introduction to AI in Higher Education_draft.pptxpboyjonauth

18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdfssuser54595a

Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha

_Math 4-Q4 Week 5.pptx Steps in Collecting DataJhengPantaleon

Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique

Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth

Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD

SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxiammrhaywood

Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching

Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron

Software Engineering Methodologies (overview)eniolaolutunde

How to Make a Pirate ship Primary Education.pptxmanuelaromero2013

APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management

Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Celine George

Código Creativo y Arte de Software | Unidad 1Maestría en Comunicación Digital Interactiva - UNR

POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar

A Critique of the Proposed National Education Policy ReformChameera Dedduwage

Concept of Vouching. B.Com(Hons) /B.CompdfUmakantAnnand

Science 7 - LAND and SEA BREEZE and its CharacteristicsKarinaGenton

BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy

Automatic Projector Calibration with Embedded Light Sensors

1. Automatic Projector Calibration with Embedded Light Sensors Ph.D. Johnny C. Lee Ph.D. Paul H. Dietz Ph.D. Dan Maynes-Aminzade Ph.D. Ramesh Raskar Ph.D. Rogerio Mallet Ph.D. Uli Dieter Carnegie Mellon University Mitsubishi Electric Research Labs Stanford University Äachen Universität Fraunhöfer Gesellschaft

2. Introduction to Projection

3. Introduction to Projection

4. Projector Calibration

5. Projector Calibration

7. Calibration Demo Demonstration of calibration process

9. Binary Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 0111 0101 0100 1100 1101 1111 1110 1010 1011 1001 1000

10. Binary Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 0111 0101 0100 1100 1101 1111 1110 1010 1011 1001 1000

11. Binary Gray

12. Binary Gray

13. Binary Gray

14. Binary Gray

15. Binary Gray

16. Binary Gray

17. Binary Gray

18. Binary Gray

19. Binary Gray

20. Binary Gray

21. Binary Gray

22. Binary Gray

23.

24. Angular Robustness & Mirrors Demonstration Video

25. Optical Path Optical path between the projector and the sensor does not need to be known. Pixel location of a sensor can be found so long as there exists a path. Additional sensors in the target surface can increase robustness to partial occlusion.

26. Application Demonstrations Demonstration Video

27. Research Applications Everywhere Displays Digital Merchandising ShaderLamps, projector AR

28.

29.

30.

31.

32.

33.

34.

Automatic Projector Calibration with Embedded Light Sensors

Recomendados

Recomendados

Mais conteúdo relacionado

Mais procurados

Mais procurados (19)

Semelhante a Automatic Projector Calibration with Embedded Light Sensors

Semelhante a Automatic Projector Calibration with Embedded Light Sensors (20)

Último

Último (20)

Automatic Projector Calibration with Embedded Light Sensors