Interactive Point-based Modeling of Complex Objects from Images Pierre Poulin (a,b) Marc Stamminger (a,c) François Duranleau (b) Marie-Claude Frasson (a) George Drettakis (a) (a) REVES, INRIA Sophia Antipolis (b) DIRO, Université de Montréal (c) University of Erlangen

Modeling Complex Objects

High visual complexity Time consuming Algorithms for specialized objects –e.g., plants, mountains, etc. Adaptive rendering Many applications need such objects

Key Observations Extracting complex models from photos is a very powerful approach Point-based representation is very effective for complex models –Efficient display and storage User interaction is beneficial when extracting quality models –Specify where details are needed –Resolve some ambiguities

Image-based Point Modeling Images are very flexible –Reality-based (photos) –Acquisition is easy

Image-based Point Modeling Points are very flexible –Fast rendering (hardware support) –Adaptive rendering for interactive display Stamminger

Image-based Point Modeling Points are very flexible –Hierarchical organization and levels of detail Q-splat

Image-based Point Modeling Points are very flexible –Visual quality –Many recent advances Deussen

Automatic Reconstruction Images Reconstruction Process Constraints 3D Model Image

Interactive Reconstruction Images Reconstruction Process Constraints 3D Model Image User new images requantize recalibrate

Interactive Reconstruction Images Reconstruction Process Constraints 3D Model Image User color comparisons plausibility threshold new depth maps zone of interest

Interactive Reconstruction Images Reconstruction Process Constraints 3D Model Image User revalidate the points request more points decimate the points jitter the points sample with patterns hole filling

Interactive Reconstruction Images Reconstruction Process Constraints 3D Model Image User undo changes remove points add polygons

Interactive Reconstruction Interactive display –6 M points/sec. on a PIII 1GHz with GeForce3 Efficient reconstruction algorithm –Test more than 1K points/sec. Simple and intuitive controls –Direct interaction with the points

Computer Vision Contributions 3D scanners Structured light Stereo – N-views Shape-from-X Volumetric

Volumetric Reconstruction Voxel coloring and Space carving –If a voxel is impossible, carved out of object –Silhouettes, transparency, shading –Photo-consistency SeitzKutulakos

Image-based Polygon Modeling Academic: Façade, Rekon, Reality Industry: RealViz, Canoma, Photomodeler Façade

Image-based Polygon Modeling Small polygonal scene ( polygons) Extracted textures and illumination Boivin

Input Images (4/14)

Input Images Digital camera: Canon EOS-DS x720 and 2166x1440 Fixed aperture and shutter speed Try not to change zoom OpenGL and ray traced test scenes

Camera Calibration

ImageModeler from RealViz Fiduciary marks placed around the object Interactive system Intrinsic and extrinsic camera parameters

3D Zone of Interest

Initial Random Points

Generated randomly within the envelope More specific patterns discussed later Projection of a point in each photo Gather colors

Color Comparison Euclidean distance –RGB, CIE xy, CIE Luv, CIE Lab –Speed vs. accuracy Color quantized images –Precomputed (ppmquantall or more sophisticated) –Quantization only on projected zone of interest –32 to 128 colors –Reduce shading variations –Efficient test for color equality

C: 25% B: 50% Dominant Color A: 100% Plausibility 100% 33% with visibility

Random Points with Depth Maps

Depth Maps Computed from the current set of points Updated on user demand With depth maps, can raise the plausibility threshold Generate more points within the object Re-evaluation of previously generated points

Clean-up Points

In general –Increase color threshold and re-evaluate With good depth maps –Project in each image –Reject if point visible and color too different

Generate More Points

Randomly Stratified sampling based on voxels Point decimation based on voxels

Guide the Points

Smaller 3D sphere of interest –Generate more points –Eliminate all points 3D flood fill for branching patterns Patterns for planar surfaces Patterns for boundary surfaces

Filling with no Leaves

Filling with Leaves

Jitter the Points

Reprojection

Stepping through it again

Results SceneImagesResolutionColorsPoints Fruit bowl13512x512-- Soldier132160x K Snack81440x K Ficcus132160x K

Synthetic Fruit Bowl ray tracingcolor pointsreprojection

Toy Soldier color points reprojection

Snack

Ficcus

Conclusions Point-based reconstruction of complex objects from images Tight integration –3D color point representation –User-driven and/or automatic reconstructions –Interactive display Flexible to integrate most advances in computer vision

Findings First steps are encouraging, but objects are still of limited realism Information in photos is inspiring, but also difficult to analyse correctly How many things in a pixel? How many pixels and colors for an object?

Future Work Video sequences High dynamic range photos Shadows and shading in color comparison Extraction of limited BRDFs 3D texture synthesis of materials

Questions Did you… Is it… Can you… When… What… Where…

User Interaction in Modeling Specify regions of interest, thresholds, validity Control the visual quality Iterative refining process Guide the solution Automatic or interactive process Interactive display (6 M points/sec. GeForce3)

Image-based Point Modeling Difficulties with points –Visibility Holes in surfaces, size of points Filtering the representation and the texture Not our goal to fix these difficulties for now

LOD in Graphics Environment maps Billboards Textured polygons Layer-depth images Light field / lumigraph

3D Scanners Very good results in general Size of the scanner wrt object Costs Fixed illumination

Stereo - N views Camera calibration Epipolar constraints Color matching 3D position and color Difficulties –Holes and occlusions –Sharp edges, noise, shading Infinity of shapes in general Targeted for object recognition and collision avoidance Only recently goal of photo-realism

Shape-from-X Silhouettes Shadows Focus/defocus Motion Shading etc.