Shape recovery from reflection.

by Yingli Tian.Thesis (Ph.D.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 202-222).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Physics-Based Shape Recovery Techniques --- p.3Chapter 1.2 --- Proposed Approaches to Shape Recovery in this Thesis --- p.9Chapter 1.3 --- Thesis Outline --- p.13Chapter 2 --- Camera Model in Color Vision --- p.15Chapter 2.1 --- Introduction --- p.15Chapter 2.2 --- Spectral Linearization --- p.17Chapter 2.3 --- Image Balancing --- p.21Chapter 2.4 --- Spectral Sensitivity --- p.24Chapter 2.5 --- Color Clipping and Blooming --- p.24Chapter 3 --- Extended Light Source Models --- p.27Chapter 3.1 --- Introduction --- p.27Chapter 3.2 --- A Spherical Light Model in 2D Coordinate System --- p.30Chapter 3.2.1 --- Basic Photometric Function for Hybrid Surfaces under a Point Light Source --- p.32Chapter 3.2.2 --- Photometric Function for Hybrid Surfaces under the Spher- ical Light Source --- p.34Chapter 3.3 --- A Spherical Light Model in 3D Coordinate System --- p.36Chapter 3.3.1 --- Radiance of the Spherical Light Source --- p.36Chapter 3.3.2 --- Surface Brightness Illuminated by One Point of the Spher- ical Light Source --- p.38Chapter 3.3.3 --- Surface Brightness Illuminated by the Spherical Light Source --- p.39Chapter 3.3.4 --- Rotating the Source-Object Coordinate to the Camera- Object Coordinate --- p.41Chapter 3.3.5 --- Surface Reflection Model --- p.44Chapter 3.4 --- Rectangular Light Model in 3D Coordinate System --- p.45Chapter 3.4.1 --- Radiance of a Rectangular Light Source --- p.45Chapter 3.4.2 --- Surface Brightness Illuminated by One Point of the Rect- angular Light Source --- p.47Chapter 3.4.3 --- Surface Brightness Illuminated by a Rectangular Light Source --- p.47Chapter 4 --- Shape Recovery from Specular Reflection --- p.54Chapter 4.1 --- Introduction --- p.54Chapter 4.2 --- Theory of the First Method --- p.57Chapter 4.2.1 --- Torrance-Sparrow Reflectance Model --- p.57Chapter 4.2.2 --- Relationship Between Surface Shapes from Different Images --- p.60Chapter 4.3 --- Theory of the Second Method --- p.65Chapter 4.3.1 --- Getting the Depth of a Reference Point --- p.65Chapter 4.3.2 --- Recovering the Depth and Normal of a Specular Point Near the Reference Point --- p.67Chapter 4.3.3 --- Recovering Local Shape of the Object by Specular Reflection --- p.69Chapter 4.4 --- Experimental Results and Discussions --- p.71Chapter 4.4.1 --- Experimental System and Results of the First Method --- p.71Chapter 4.4.2 --- Experimental System and Results of the Second Method --- p.76Chapter 5 --- Shape Recovery from One Sequence of Color Images --- p.81Chapter 5.1 --- Introduction --- p.81Chapter 5.2 --- Temporal-color Space Analysis of Reflection --- p.84Chapter 5.3 --- Estimation of Illuminant Color Ks --- p.88Chapter 5.4 --- Estimation of the Color Vector of the Body-reflection Component Kl --- p.89Chapter 5.5 --- Separating Specular and Body Reflection Components and Re- covering Surface Shape and Reflectance --- p.91Chapter 5.6 --- Experiment Results and Discussions --- p.92Chapter 5.6.1 --- Results with Interreflection --- p.93Chapter 5.6.2 --- Results Without Interreflection --- p.93Chapter 5.6.3 --- Simulation Results --- p.95Chapter 5.7 --- Analysis of Various Factors on the Accuracy --- p.96Chapter 5.7.1 --- Effects of Number of Samples --- p.96Chapter 5.7.2 --- Effects of Noise --- p.99Chapter 5.7.3 --- Effects of Object Size --- p.99Chapter 5.7.4 --- Camera Optical Axis Not in Light Source Plane --- p.102Chapter 5.7.5 --- Camera Optical Axis Not Passing Through Object Center --- p.105Chapter 6 --- Shape Recovery from Two Sequences of Images --- p.107Chapter 6.1 --- Introduction --- p.107Chapter 6.2 --- Method for 3D Shape Recovery from Two Sequences of Images --- p.109Chapter 6.3 --- Genetics-Based Method --- p.111Chapter 6.4 --- Experimental Results and Discussions --- p.115Chapter 6.4.1 --- Simulation Results --- p.115Chapter 6.4.2 --- Real Experimental Results --- p.118Chapter 7 --- Shape from Shading for Non-Lambertian Surfaces --- p.120Chapter 7.1 --- Introduction --- p.120Chapter 7.2 --- Reflectance Map for Non-Lambertian Color Surfaces --- p.123Chapter 7.3 --- Recovering Non-Lambertian Surface Shape from One Color Image --- p.127Chapter 7.3.1 --- Segmenting Hybrid Areas from Diffuse Areas Using Hue Information --- p.127Chapter 7.3.2 --- Calculating Intensities of Specular and Diffuse Compo- nents on Hybrid Areas --- p.128Chapter 7.3.3 --- Recovering Shape from Shading --- p.129Chapter 7.4 --- Experimental Results and Discussions --- p.131Chapter 7.4.1 --- Simulation Results --- p.131Chapter 7.4.2 --- Real Experimental Results --- p.136Chapter 8 --- Shape from Shading under Multiple Extended Light Sources --- p.142Chapter 8.1 --- Introduction --- p.142Chapter 8.2 --- Reflectance Map for Lambertian Surface Under Multiple Rectan- gular Light Sources --- p.144Chapter 8.3 --- Recovering Surface Shape Under Multiple Rectangular Light Sources --- p.148Chapter 8.4 --- Experimental Results and Discussions --- p.150Chapter 8.4.1 --- Synthetic Image Results --- p.150Chapter 8.4.2 --- Real Image Results --- p.152Chapter 9 --- Shape from Shading in Unknown Environments by Neural Net- works --- p.167Chapter 9.1 --- Introduction --- p.167Chapter 9.2 --- Shape Estimation --- p.169Chapter 9.2.1 --- Shape Recovery Problem under Multiple Rectangular Ex- tended Light Sources --- p.169Chapter 9.2.2 --- Forward Network Representation of Surface Normals --- p.170Chapter 9.2.3 --- Shape Estimation --- p.174Chapter 9.3 --- Application of the Neural Network in Shape Recovery --- p.174Chapter 9.3.1 --- Structure of the Neural Network --- p.174Chapter 9.3.2 --- Normalization of the Input and Output Patterns --- p.175Chapter 9.4 --- Experimental Results and Discussions --- p.178Chapter 9.4.1 --- Results for Lambertian Surface under One Rectangular Light --- p.178Chapter 9.4.2 --- Results for Lambertian Surface under Four Rectangular Light Sources --- p.180Chapter 9.4.3 --- Results for Hybrid Surface under One Rectangular Light Sources --- p.190Chapter 9.4.4 --- Discussions --- p.190Chapter 10 --- Summary and Conclusions --- p.191Chapter 10.1 --- Summary Results and Contributions --- p.192Chapter 10.2 --- Directions of Future Research --- p.199Bibliography --- p.20

Direct Differential Photometric Stereo Shape Recovery of Diffuse and Specular Surfaces

This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s10851-016-0633-0Recovering the 3D shape of an object from shading is a challenging problem due to the complexity of modeling light propagation and surface reflections. Photometric Stereo (PS) is broadly considered a suitable approach for high-resolution shape recovery, but its functionality is restricted to a limited set of object surfaces and controlled lighting setup. In particular, PS models generally consider reflection from objects as purely diffuse, with specularities being regarded as a nuisance that breaks down shape reconstruction. This is a serious drawback for implementing PS approaches, since most common materials have prominent specular components. In this paper, we propose a PS model that solves the problem for both diffuse and specular components aimed at shape recovery of generic objects with the approach being independent of the albedo values thanks to the image ratio formulation used. Notably, we show that by including specularities, it is possible to solve the PS problem for a minimal number of three images using a setup with three calibrated lights and a standard industrial camera. Even if an initial separation of diffuse and specular components is still required for each input image, experimental results on synthetic and real objects demonstrate the feasibility of our approach for shape reconstruction of complex geometries.The first author acknowledges the support of INDAM under the GNCS research Project “Metodi numerici per la regolarizzazione nella ricostruzione feature-preserving di dati.

Recovery of surface orientation from diffuse polarization

When unpolarized light is reflected from a smooth dielectric surface, it becomes partially polarized. This is due to the orientation of dipoles induced in the reflecting medium and applies to both specular and diffuse reflection. This paper is concerned with exploiting polarization by surface reflection, using images of smooth dielectric objects, to recover surface normals and, hence, height. This paper presents the underlying physics of polarization by reflection, starting with the Fresnel equations. These equations are used to interpret images taken with a linear polarizer and digital camera, revealing the shape of the objects. Experimental results are presented that illustrate that the technique is accurate near object limbs, as the theory predicts, with less precise, but still useful, results elsewhere. A detailed analysis of the accuracy of the technique for a variety of materials is presented. A method for estimating refractive indices using a laser and linear polarizer is also given

Structural and Magnetic Dynamics in the Magnetic Shape Memory Alloy Ni2_2MnGa

Magnetic shape memory Heusler alloys are multiferroics stabilized by the correlations between electronic, magnetic and structural order. To study these correlations we use time resolved x-ray diffraction and magneto-optical Kerr effect experiments to measure the laser induced dynamics in a Heusler alloy Ni$_2$MnGa film and reveal a set of timescales intrinsic to the system. We observe a coherent phonon which we identify as the amplitudon of the modulated structure and an ultrafast phase transition leading to a quenching of the incommensurate modulation within 300~fs with a recovery time of a few ps. The thermally driven martensitic transition to the high temperature cubic phase proceeds via nucleation within a few ps and domain growth limited by the speed of sound. The demagnetization time is 320~fs, which is comparable to the quenching of the structural modulation.Comment: 5 pages, 3 figures. Supplementary materials 5 pages, 5 figure

Inverse scattering for vowel articulation with frequency-domain data

An inverse scattering problem is analyzed for vowel articulation in the human vocal tract. When a unit amplitude, monochromatic, sinusoidal volume velocity is sent from the glottis towards the lips, various types of scattering data are used to examine whether the cross sectional area of the vocal tract can uniquely be determined by each data set. Among the data sets considered are the absolute value of the pressure measured at a microphone placed at some distance from the lips, the pressure at the lips, and the transfer function from the glottis to the lips. In case of nonuniqueness, it is indicated what additional information may be used for the unique determination.Comment: 29 pages, 9 figure

Modeling of mode-locking in a laser with spatially separate gain media

We present a novel laser mode-locking scheme and discuss its unusual properties and feasibility using a theoretical model. A large set of single-frequency continuous-wave lasers oscillate by amplification in spatially separated gain media. They are mutually phase-locked by nonlinear feedback from a common saturable absorber. As a result, ultra short pulses are generated. The new scheme offers three significant benefits: the light that is amplified in each medium is continuous wave, thereby avoiding issues related to group velocity dispersion and nonlinear effects that can perturb the pulse shape. The set of frequencies on which the laser oscillates, and therefore the pulse repetition rate, is controlled by the geometry of resonator-internal optical elements, not by the cavity length. Finally, the bandwidth of the laser can be controlled by switching gain modules on and off. This scheme offers a route to mode-locked lasers with high average output power, repetition rates that can be scaled into the THz range, and a bandwidth that can be dynamically controlled. The approach is particularly suited for implementation using semiconductor diode laser arrays.Comment: 13 pages, 5 figures, submitted to Optics Expres

Towards dynamic camera calibration for constrained flexible mirror imaging

Flexible mirror imaging systems consisting of a perspective camera viewing a scene reflected in a flexible mirror can provide direct control over image field-of-view and resolution. However, calibration of such systems is difficult due to the vast range of possible mirror shapes and the flexible nature of the system. This paper proposes the fundamentals of a dynamic calibration approach for flexible mirror imaging systems by examining the constrained case of single dimensional flexing. The calibration process consists of an initial primary calibration stage followed by in-service dynamic calibration. Dynamic calibration uses a linear approximation to initialise a non-linear minimisation step, the result of which is the estimate of the mirror surface shape. The method is easier to implement than existing calibration methods for flexible mirror imagers, requiring only two images of a calibration grid for each dynamic calibration update. Experimental results with both simulated and real data are presented that demonstrate the capabilities of the proposed approach

Effects of seawalls on the adjacent beach

This study was carried out to examine the effects of seawalls on the adjacent beach by three dimensional model test. The results obtained from model test were analyzed in terms of volumetric changes and shoreline and hydrographic change to quantify the effects of seawalls. The experiments were carried out in the wave basin of Coastal and Oceanographic Engineering department, University of Florida. A model seawall was installed on the test beach (19mxl4m) which was initially molded into equilibrium shapes. During the test, hydrographic surveys were conducted at regular time intervals. The main variable in the experiment is the wave angle. Cases both with and without seawall were tested. (141pp.