We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byJoe Lauderdale
Modified about 1 year ago
Micro Phase Shifting Se-Hoon, Park -Mohit Gupta and Shree K. Nayar, CVPR2012
2 Real-Time Compressive Tracking Contents Phase shifting Phase shift encoding Phase shift decoding Issue Inter reflection Micro Phase shifting Disambiguation experiments
Phase shifting Phase shift encoding Three image structured light I1(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y) - 2π/3] I2(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y)] I3(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y) + 2π/3] I1(x,y) : first imageI2(x,y) : seond imageI3(x,y) : third image I’(x,y) : average intensityI’’(x,y) : intensity modulationθ(x,y) : phase
Phase shifting Phase shift encoding Ex) I’(x,y) = 125 I’’(x,y) = 125 I1(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y) - 2π/3] I2(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y)] I3(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y) + 2π/3] θ(x,y)I1(x,y)I2(x,y)I3(x,y) π/ π/ π/ π/ π/ π 1870
Phase shift encoding Phase shifting 55 I1I2I3
Phase shifting I1(x,y)I2(x,y)I3(x,y)θ(x,y) π/ π/ π/ π/ π/ π
Phase shifting Phase shift decoding Camera image Projector image
Phase shift decoding –If the noise is same in the three camera images, noise doesn’t matter. Phase shifting 8
9 pixel pixel θ (π) θ (π) Input phase output phase ambiguous I1(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y) - 2π/3] I2(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y)] I3(x,y) = I’(x,y) + I’’(x,y)cos[θ(x,y) + 2π/3] Input phase Output phase
Phase shifting 10 frequency ( ) amplitude Broad Frequency Band max mean min Unambiguous but Noisy Accurate but Ambiguous
Inter reflection Issue 11 camera projector Inter reflections P Q R time Inter reflections Direct Radiance radiance scene
Inter reflection Issue 12 camera projector Inter reflections P Q R time Inter reflections Direct Radiance radiance scene Phase Error
Inter reflection Issue 13 camera projector Inter reflections P Q R scene Inter reflection Illumination pattern light transport coefficients
Inter reflection Issue 14 camera projector Inter reflections P Q R scene Inter reflection Illumination pattern light transport coefficients
Inter reflection Issue 15 camera projector Inter reflections P Q R scene Inter reflection Illumination pattern light transport coefficients
Inter reflection Issue 16 camera projector Inter reflections P Q R scene Inter reflection Illumination pattern light transport coefficients N
Inter reflection Issue 17 Inter reflection * illumination patternlight transport coefficients pixels
Inter reflection Issue 18 frequency projected patterns Inter reflection illumination patternlight transport coefficients
Inter reflection Issue 19 frequency projected patterns Inter reflection illumination patternlight transport coefficients Micro phase shifting
Micro Phase shifting 20 max mean min frequency ( ) amplitude How Can We Disambiguate Phase Without Low Frequency Patterns?
Micro Phase shifting 21 number of periods (unknown) Phase disambiguation
Micro Phase shifting 22 unknownknownunknownknownunknownknown
Micro Phase shifting 23
Micro Phase shifting 24 Experiments –Ceramic bowl
Micro Phase shifting 25 Experiments –Ceramic bowl point projector
Micro Phase shifting 26 Experiments –Ceramic bowl Conventional Phase Shifting Micro Phase Shifting [Our]
Micro Phase shifting 27 Experiments –Lemon point projector subsurface scacttering
Experiments –Lemon Micro Phase shifting 28 Conventional Phase Sh ifting Micro Phase Shifting [Our]
Experiments –Shiny Metal Bowl Micro Phase shifting 29
Experiments –Shiny Metal Bowl Micro Phase shifting 30 Conventional Phase Shi fting Micro Phase Shifting [Our]
Spherical Harmonic Lighting Jaroslav Křivánek. Overview Function approximation Function approximation Spherical harmonics Spherical harmonics Some other.
MIT 2.71/2.710 Optics 10/27/04 wk8-b-1 The imaging problem object imaging optics (lenses, etc.) image.
Light, Reflectance, and Global Illumination TOPICS: Survey of Representations for Light and Visibility Color, Perception, and Light Reflectance Cost of.
Ch. 14 Science Vocabulary Preview. compression A compression is the party of the sound wave where the particles are bunched together.
EET260: A/D and D/A conversion Conversion from analog to digital We will consider the problem of converting an analog waveform into binary values and.
William A.P. Smith and Edwin R. Hancock Department of Computer Science, University of York, UK CVPR 2009 Reporter: Annie Lin.
P y L r1r1 r2r2 Q s1s1 s2s2 d O Barrier with slits Screen Geometrical analysis of Youngs Double Slit Experiment: What is the cause of the interference.
Ter Haar Romeny, EMBS Berder 2004 How can we find a dense optic flow field from a motion sequence in 2D and 3D? Many approaches are taken: - gradient based.
1 P1X: Optics, Waves and Lasers Lectures, Lecture 4: Interference and diffraction of light (I) Youngs two slit experiment (Y&F 35.2) o To observe.
Photometric Image Formation CSE 559: Computer Vision Guest Lecturer: Austin Abrams Images/Demo from Steve Seitz, Wikipedia.
Geology 5640/6640 Seismology Last time: Surface Waves Surface waves (evanescent waves trapped at a surface) include Stoneley, Lamb as well as Rayleigh,
EE2F2 - Music Technology 4. Effects. Effects (FX) Effects are applied to modify sounds in many ways – we will look at some of the more common Effects.
Polaris Coordinates of a Vector How can we represent a vector? -We plot an arrow: the length proportional to magnitude of vector the line represents the.
Bayesian Belief Propagation Reading Group. Overview Problem Background Bayesian Modelling Bayesian Modelling Markov Random Fields Markov Random Fields.
A simplified artist interface Physically Based Shading Niklas Hansson Head Teacher Game programming The Game Assembly.
A Projective Framework for Radiometric Image Analysis CVPR 2009 Date: 2010/3/9 Reporter : Annie lin.
Fast, Arbitrary BRDF Shading for Low-Frequency Lighting Using Spherical Harmonics Jan Kautz, MPI Informatik Peter-Pike Sloan, Microsoft Research John Snyder,
Digital Image Processing Manipulation of Digital Images by computers. Pre processing / Image Restoration Image Enhancement Information Extraction.
If you have not watched the PowerPoint on the unit circle you should watch it first. After youve watched that PowerPoint you are ready for this one. If.
Robot Vision SS 2009 Matthias Rüther 1 ROBOT VISION Lesson 7: State of the Art in 3D Reconstruction Matthias Rüther.
Computer Graphics - Shading - Hanyang University Jong-Il Park.
JPEG Compresses real images Standard set by the Joint Photographic Experts Group in 1991.
Convolutional Codes Mohammad Hanaysheh Mahdi Barhoush.
The Radiance Equation. Motivation Photo realistic image rendering is particularly difficult to compute because of the complexity of the physical nature.
Young Modulus Example The pairs (1,1), (2,2), (4,3) represent strain (millistrains) and stress (ksi) measurements. Estimate Young modulus using the three.
Trigonometric Functions – Lesson 3 REVIEW: Graph Sine and Cosine Functions With amplitude and period changes. INVESTIGATE” VERTICAL SHIFT Objective: To.
Ch Waves & Sound I. Characteristics of Waves Waves Transverse waves Longitudinal waves Measuring waves.
Oscillations and Simple Harmonic Motion: AP Physics C: Mechanics.
The Film Camera. Camera Basics A still film camera is made of three basic elements: an optical element (the lens), an optical element (the lens), a chemical.
Precomputed Radiance Transfer for Real-Time Rendering in Dynamic, Low-Frequency Lighting Environments Peter-Pike Sloan, Microsoft Research Jan Kautz, MPI.
© 2016 SlidePlayer.com Inc. All rights reserved.