Visual Appearance: Reflectance Transformation Imaging (RTI) 28 Aprile 2016
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1 Visual Appearance: Reflectance Transformation Imaging (RTI) 28 Aprile 2016
2 Visual Appearance
3 LIGHT MATERIAL Visual Appearance Color due to the interaction between the lighting environment (intensity, position, ) and the properties of the object surface and material.
4 Visual Appearance: why? Photorealistic rendering High fidelity reproduction of the real world PHOTO RENDERING
5 Visual Appearance: why? Perception Better understanding of the details (even with a fake appearance)
6 Visual Appearance: why? To infer more cognitive data from color details
7 Visual Appearance: Definition Reflectance Scattering Function (12D) (Light and view direction, Incident and outgoing surface point Wavelength, Time)
8 Visual Appearance: Definition Reflectance Scattering Function (12D) No mathematical formulation Measurement impractical Simplification by constrains on the set of possible reflectance effects Phosphorescence Fluorescence Subsurface scattering Specular scattering Backscattering Diffuse scattering
9 Visual Appearance: Definition
10 Visual Appearance BSSRDF (8D) No fluorescence (no wavelength change) No Phosphorescence (zero time light transport) Subsurface scattering (translucent material)
11 Visual Appearance SVBRDF (6D) No Subsurface scattering (translucent material) Opaque material (reflection on the same place) Spatially varying glossy material
12 Visual Appearance BRDF (4D) No spatially varying Uniform material
13 Visual Appearance Light Field (4D) Amount of light faring in every direction through every point in space (simplified plenoptic function) Fixed lighting condition and variable view direction Spatially varying Image-based rendering (no geometry) Surface Reflectance Field (4D) Fixed view position and variable light direction Spatially varying Image-based relighting (RTI) Implicit geometry
14 Visual Appearance: how to use? BSSRDF and BRDF Model-based rendering Explicit geometry Modeling or acquisition of the appearance Global illumination algorithm More precise but computational heavy Light Field and Reflectance Field Image based rendering Set of photos ( interpolation ) No geometry or implicit geometry Realistic rendering but trade-off between data and precision
15 Reflectance Transformation Imaging (RTI)
16 RTI: Overview Technique for the estimation of the Reflectance 2001 HP Labs Polynomial Texture Map New type of texture mapping with the possibility to change the light direction in an interactive way Presented as a powerful tool to improve the study of ancient writings and inscriptions.
17 RTI: Overview Multiple digital photos taken from a stationary camera with different know light directions 2D image that synthesizes the surface lighting information for each pixel with a mathematical model Capture the subject s surface shape (implicit geometry) and colour Enable the interactive relighting of the subject from any direction
18 RTI: Overview
19 RTI: Overview
20 RTI: Overview
21 RTI Format Polynomial Texture Map (PTM) Bi-quadratic polynomial to model the variation of the pixel color in function of the light direction LRGB PTM (6 coefficients a0... a5 + RGB color) RGB PTM (18 coefficients a0...a5 for each color channel)
22 RTI Format Hemispherical Harmonics Map (HSH) Linear combination of first nine Hemispherical Harmonics function for each color channel of each pixel (9 coefficients for each color channel)
23 RTI: PTM vs HSH PTM Lower contrast Fail to capture important specular component Poor results on reflective material (gold or silver) HSH Higher contrast Better representation of the specular component More photorealistic results with highly reflective material
24 N + 1 Photo RTI: Computation INPUT A set of (n+1) photo acquired from a fixed position with a different position of a directional light Light direction for each photo OUTPUT Function coefficient for each pixel by solving an overdetermined linear system using Singular Value Decomposition HSH EXAMPLE? Color vector
25 RTI: Acquisition DOME Pro Set of light in fixed position Automatic and fast acquisition Con Limitation on the maximum object size
26 RTI: Acquisition DOME
27 RTI Acquisition Arm with 12 flash National Gallery of London Manual Template Rig Cultural Heritage Imaging
28 RTI: Acquisition for large object PTM PLANNER Virtual Dome Producing the position in the space of the light for the acquisition of the RTI starting from some info of the object (size and height from the floor) and the position of the camera
29 RTI: Acquisition for large object Plumb line Halogen floodlight 1000W 8 Mpixel digital camera Boom stand Plan with the light direction tripod
30 RTI: Acquisition for large object Reflective sphere Free movement of the light in front of the object Tool able to find the light direction from the photo in a semi automatic way using the highlight (LPTracker) Sphere diameter in the image must be at least 200 pixels wide to obtain good result
31 RTI: Processing 1. Correction of small misalignment in the set of photos due to movement of the camera using the tool for the creation of panoramic images 2. Image correction (white balance, crop) 3. Estimation of the light direction (LPTracker) 4. Generation of the final RTI (PTMFitter or RTIBuilder)
32 RTI: Acquisition and Processing Guide, tutorial, video and software for the acquisition and processing of RTI images Live acquisition in the next lesson
33 RTI: Results Tomb of the Archbishop Giovanni Scherlatti, made by Nino Pisano, Museo dell Opera Primaziale di Pisa, XIV Sec. Size: 70 x 80 cm, 105 photos, acquisition with PTMPlanner 3.5h, PTM
34 RTI: Results Roman Sarcophagus II Sec. DC, legend of Fedra and Ippolito, Camposanto Monumentale, Pisa Size: 100 x 70 cm, 66 photos, acquisition with PTMPlanner about 2 h, PTM
35 RTI: Results Silver Ducato Pisa Museo di San Matteo, Pisa Diameter 41.5 mm, 256 photos, Dome in about 10 minute, HSH
36 RTI: Implicit geometry Computation of the surface normal for each pixel under the assumption of Lambertian reflection Photometric stereo? l 1 l 2 n l l m Light direction that maximizes the reflectance function
37 RTI: Implicit geometry 3D Scanning Vs. PTM Smoother normal but coherent value
38 RTI: Visualization RTIViewer Developed by Visual Computing Lab, ISTI-CNR. PTM and HSH Multi-view RTI Rendering Modes Snapshots From version 1.1: Annotation Download Link:
39 RTI: Visualization RTIViewer - Multi-view RTI (Experimental) Interactive change of the view position Collection of RTI images taken from different positions Flow data to interpolate the viewpoint between two RTI images (optional) VIEW 1 VIEW 2
40 RTI: Rendering modes Improve the examination of the details and shapes: Diffuse Gain (PTM) Specular Enhancement (PTM and HSH) Unsharp Masking (PTM) Normal UM Luminance UM Coefficient UM Multi-Light Detail Enhancement (PTM) Dynamic and static version
41 RTI: Rendering modes Diffuse Gain Increase the directional sensitivity of the surface to the light changing Gain parameter to increase and decrease the effect Results Enhancement inscription
42 RTI: Rendering modes DEFAULT RENDERING DIFFUSE GAIN
43 RTI: Rendering modes Specular Enhancement Add specular effect to the image changing the reflectance properties of the surface: Original color (parameter Kd) Specularity (parameter Ks) Shininess (parameter n) Results Enhancement inscription
44 RTI: Rendering modes SPECULAR ENHANCEMENT DEFAULT RENDERING
45 RTI: Rendering modes Unsharp Masking Enhance the high frequency details to increase the edge contrast of the image ORIGINAL IMAGE I SMOOTHED IMAGE I S ENHANCED IMAGE I E
46 RTI: Rendering modes Unsharp Masking Gain parameter k to select the amount of enhancement Image Unsharp Masking Normal Unsharp Masking Luminance Unsharp Masking Coefficient Unsharp Masking
47 RTI: Rendering modes Normal Unsharp Masking DEFAULT RENDERING NORMAL UM
48 RTI: Rendering modes Luminance Unsharp Masking DEFAULT RENDERING LUMINANCE UM
49 RTI: Rendering modes Luminance vs Image Unsharp Masking Depth discontinuities are amplified Color discontinuities are not exacerbate LUMINANCE UM IMAGE UM
50 RTI: Rendering modes Coefficient Unsharp Masking DEFAULT RENDERING COEFFICIENT UM
51 RTI: Rendering modes Multi-Light Detail Enhancement Using different light direction for each area of the RTI image in order to enhance the surface details Per-tile light direction maximizing an energy function (local sharpness S and brightness Y with a parameter alpha to tune their ratio) Final interpolation to compute the per-pixel light direction Dynamic Enhancement (local perturbation of the light direction chosen by the user) Static Enhancement (static image sampling all possible light directions )
52 RTI: Rendering modes Dynamic Multi-Light Enhancement DEFAULT RENDERING DYNAMIC MULTI-LIGHT
53 RTI: Rendering modes Static Multi-Light Enhancement STATIC MULTI-LIGHT DEFAULT RENDERING
54 RTI on the WEB Visualization of RTI images in the next generation of web browsers in an interactive way (WebGL + SpiderGL) WebGL (Safari, Firefox and Chrome) Graphics API for Javascript to use the GPU capabilities in the web browser without install external plugins SpiderGL Javascript library to develop 3D web application based on WebGL DEMO
55 RTI on the WEB Issues Pre-processing of the RTI image to build a hierarchical layout to store in the web server (multi-resolution and multi-layer quad-tree) Algorithm to visit the hierarchy Loading the node of hierarchy asynchronously
56 RTI: Application Employed in several Cultural Heritage projects Palaeontology (high relief fossil, ancient stone tool) Surface textures of oil paintings (National Gallery and Tate Gallery of London ) Numismatic collection Antikythera Mechanism
57 RTI: Pro and Con PRO Compact structure Fast and easy acquisition Few post-processing Realistic rendering result Bas-relief or similar Implicit geometry or material Detail Enhancement CONTRO Fixed point of view Approximation No object with big depth discontinues Max size of the object
58 RTI: Not only Reflectance Encoding other attribute Depth of focus Time varying effect
59 Storytelling of a coin collection by means of RTI: Palazzo Blu and Museo Nazionale di San Matteo
60 The project Rational Presenting to the public a collection of coins in an innovative way Why? Coins are very small artworks, presented from a distance(>50 cm), only one side visible They don t tell their story by themselves Who? National San Matteo Museum and VCG, Pisa, Italy
61 The project Virtual inspection of coins. How to manage it? Rotate the coin under directional illumination, to help our brain to build a cognitive model by inferring data from dynamic reflection and shading A representation to simulate in real time the illumination effects in an accurate manner ATTENTION!!! Extremely complex to produce images of coins due to the reflection effects of different materials
62 Idea Project Design and implementation of an interactive kiosk to allow the presentation and the virtual inspection of coins: Easy to use for the user Ordinary (inexpert) public Interactive manipulation Zooming, panning, rotating the coin, changing the light direction Telling their story throw multimedia data Organization in several overlapping subset Descriptive data for specific location on the coin
63 Virtual Inspection: 3D vs 2D Solutions 3D - Geometry + Surface appearance 3D acquisition of coins is still a complex task (sides are very thin, alignment problems) Higher acquisition and processing time More expensive (complex and ad hoc instruments) 3D manipulation is more complex to understand and control for the user 2D Reflectance Transformation Imaging (RTI) techniques Relightable images Higher quality of illumination-dependent effects Higher resolution Cheaper acquisition and processing step Very easy to understand and to control for users
64 Coin kiosk Interactive kiosk Organization of the coins in categories and present these categories Virtual inspection of each coin RTI manipulation (HSH) Presentation of the coin Hotspots on selected areas to tell the story of coin s details Multi-touch screen and web site Implementation details HTML + Javascript (presentation of multimedia data) WebGL + SpiderGL (RTI visualization)
65 RTI Acquisition Subset of the museum s collection(42 coins) selected from the museum curators following value and storytelling criteria VCG Dome 4 shells, easy to assemble 116white LEDs Overhead Reflex camera (24 Mpx) Computer controlled for automatic acquisition (15 minutes per coins) Digitalization time: 2 day
66 Coin Kiosk DEMO
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