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May 20 (Thursday) - 10:15 - 11:15
Poster Session 2
10:15 - 11:15 - May 20 (Thursday)Session chair: Bob Fisher, University of Edinburgh
3D Photography and Image-based Rendering
Improving the accuracy of fast dense stereocorrespondence algorithms by enforcing local consistency of disparity fields
Stefano Mattoccia
UNIVERSITYOFBOLOGNA DEIS-ARCES, ITALY
Accurate, dense 3D reconstruction is an important requirement in many
applications, and stereo represents a viable alternative to active sensors.However, top-ranked stereo algorithms rely on iterative 2D disparityoptimization methods for energy minimization that are not well suited to the
fast and/or hardware implementation often required in practice. Anexception is represented by the approaches that perform disparityoptimization in one dimension (1D) by means of scanline optimization (SO)or dynamic programming (DP). Recent SO/DP-based approaches aim toavoid the well known streaking effect by enforcing vertical consistency
between scanlines deploying aggregated costs, aggregating multiplescanlines, or performing energy minimization on a tree. In this paper we
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Presented by Stefano Mattoccia
May 20 (Thursday) - 10:15 - 11:15
show that the accuracy of two fast SO/DP-based approaches can bedramatically improved by exploiting a non-iterative methodology that, bymodeling the coherence within neighboring points, enforces the localconsistency of disparity fields. Our proposal allows us to obtain top-ranked
results on the standard Middlebury dataset and, thanks to its computationalstructure and its reduced memory requirements, is potentially suited to fast
and/or hardware implementations.
Planar patch detection for disparity maps
Eric Bughin1, Andrs Almansa2
1CMLA - ENS CACHAN, FRANCE, 2ENST TELECOMPARISTECH, FRANCE
We propose a new parameter-free method for detecting planar patches indisparity maps. We first introduce an a contrario decision criterion which may
be used to solve two decision problems on configurations of 3D points: (i) isthe configuration well explained by a plane?; (ii) what is the optimal number
of planes that best explains the configuration? These decision criteria are thecore of an algorithm that searches for an optimal explanation of a disparity
map by planar patches whenever applicable. This method may be used for 3Dreconstruction of urban environments, particularly in the context oflow-baseline stereo where precision requirements are most strict, and apertinent choice of the type and amount of regularization is key to achieving
accurate results.
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Presented by Eric Bughin
May 20 (Thursday) - 10:15 - 11:15
Presented by Jamil Drarni
Bas-Relief Ambiguity Reduction in Shape from
Shadowgrams
Jamil Drarni1, Sbastien Roy2, Peter Sturm3
1UNIVERSITDEMONTRAL, CANADA / INRIA-RHNE-ALPES, FRANCE, 2UNIVERSITDEMONTRAL, CANADA, 3INRIA-RHNE-ALPES, FRANCE
Using shadowgrams for 3D reconstruction is inherently ambiguous. It has be
shown that this ambiguity has 4 parameters. We show that, when the lightspots are visible to the camera, the number of parameters drops to one.
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May 20 (Thursday) - 10:15 - 11:15A Probabilistic Approach to ToF and Stereo Data
FusionCarlo Dal Mutto, Pietro Zanuttigh, Guido Maria Cortelazzo
UNIVERSITYOFPADOVA, ITALY
Current 3D video applications require the availability of depth information,
that can be acquired real-time by stereo vision systems and ToF cameras. Inthis paper, a heterogeneous acquisition system is considered, made of twohigh resolution standard cameras (stereo pair) and one ToF camera. Thestereo system and the ToF camera must be properly calibrated together in
order to operate jointly. Therefore this work introduces first a generalized
multi-camera calibration technique which does not exploit only theluminance (color) information, but also the depth information extracted bythe ToF camera. A probabilistic algorithm is then derived in order to obtain
high quality depth information from the information of both the ToF cameraand the stereo-pair. Experimental results show that the proposed calibrationalgorithm leads to a very accurate calibration suitable for the fusionalgorithm, that allows for precise extraction of the depth information.
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Presented by Toby Collins
May 20 (Thursday) - 10:15 - 11:15
Single-view Perspective Shape-from-Texture withFocal Length Estimation: A Piecewise Affine Approach
Toby Collins1, Jean-Denis Durou2, Pierre Gurdjos3, Adrien Bartoli4
1UNIVERSITD'AUVERGNE,FRANCE, 2IRIT, UNIVERSITPAUL SABATIER, FRANCE&CMLA, ENS CACHAN, CNRS, UNIVERSUD, FRANCE, 3IRIT, ENSEEIHT, FRANCE,4UNIVERSITD'AUVERGNE, FRANCE
We present a new formulation to the well known problem of 3D shape-from-texture from a single image, but one which is able to handle
uncalibrated perspective cameras. Contrary to previous methods, we cast thetask as multi-plane based camera pose estimation whereby the informationprovided by a textured surface makes it possible to perform shape-from-texture and camera focal length estimation jointly. We show that by
approximating global perspective by local scaled orthography (which holdsoften in practical cases) we can acquire depth, surface orientation and focallength from a single image in closed form. This advances state-of-the-art
where a calibrated camera is nearly always assumed in order to compute 3Dshape from a single image.
A statistical illumination-reflectance separation
algorithm for the multispectral acquisition of frescoes
Anna Paviotti, Guido Maria Cortelazzo
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Presented by Guido Maria Cortelazzo
UNIVERSITYOFPADOVA, ITALY
The multispectral acquisition of frescoes poses unsolved challenges, the maindifficulty being that it is often impos- sible to measure the reference whitesignal. We propose a statistical method to estimate the illumination directlyfrom the color signal, based on a modification of the RANSAC al- gorithm.
We apply our method to the estimation of the light- ing field of threepaintings by contemporary Italian artists and of a fresco of the Castello delBuonconsiglio in Trento (Italy), for which a ground truth was available.Quanti- tative results show that the performance of our method is good in
terms of the relative mean error on illumination and reflectance, while themaximum errors are sometimes significant.
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May 20 (Thursday) - 10:15 - 11:15
Presented by Roberto Toldo
Real-time Incremental J-Linkage for RobustMultiple Structures Estimation
Roberto Toldo, Andrea Fusiello
DIPARTIMENTODIINFORMATICA - UNIVERSITDIVERONA, ITALY
This paper describes an incremental, real-time implementation of J-linkage, aprocedure that can detect multiple instances of a model from data corruptedby noise and outliers. It works in real-time, thanks to several approximationsthat have been introduced to get around the quadratic complexity of the
original algorithm.
3D Scanning Methods and Devices
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Presented by David Gallup
May 20 (Thursday) - 10:15 - 11:15
A Heightmap Model for Efficient 3DReconstruction from Street-Level Video
David Gallup1, Jan-Michael Frahm1, Marc Pollefeys2
1UNIVERSITYOFNORTHCAROLINA, USA, 2ETH ZURICH, SWITZERLAND
This paper introduces a fast approach for automatic dense large-scale 3Durban reconstruction from video. The presented system uses a novelmulti-view depthmap fusion algorithm where the surface is represented by a
heightmap. While this model seems to be a more natural fit to aerial andsatellite data, we have found it to also be a powerful representation forground-level reconstructions. It has the advantage of producing purelyvertical facades, and it also yields a continuous surface without holes.
Compared to more general 3D reconstruction methods, our algorithm ismore efficient, uses less memory, and produces more compact models atthe expense of losing some detail. Our GPU implementation can compute a
200x200 heightmap from 64 depthmaps in just 92 milliseconds. Wedemonstrate our system on a variety of challenging ground-level datasetsincluding large buildings, residential houses, and store front facadesobtaining clean, complete, compact, and visually pleasing 3D models.
?
Stripe Propagation for Color Encoded Structured
Light
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Presented by Michael Burisch
May 20 (Thursday) - 10:15 - 11:15
Michael Burisch, David Guerrero Ichaso, Arjan Kuijper
FRAUNHOFERINSTITUTEFORCOMPUTERGRAPHICSRESEARCHIGD, GERMANY
We present a 3D scanning system using color encoded structured light,which is able to reconstruct a surface using only a single image. The work is
focused on exploiting the captured data and reconstructing as many pointsas possible. Therefore a multi-stage method is presented to reconstruct thesurface from the captured pattern. It consists of i) a robust edge detectionstep, ii) a color decoding using feedback from previous stripes and iii) a
propagation step to detect errors and propagate detected stripes. Usingfeedback from neighboring stripes and propagation along the stripedirection during color detection and sequence decoding, the system is ableto recover areas where regular approaches fail, such as small bridges in
geometry, and detect and correct false classifications. Depending on surfacecomplexity we were able to achieve a significant increase in the amount ofreconstructable points.
Active Triangulation in the Outdoors: APhotometric Analysis
David Ilstrup, Roberto Manduchi
UC-SANTA CRUZ, USA
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Presented by David Ilstrup
May 20 (Thursday) - 10:15 - 11:15
Active triangulation is a well established technique for collecting rangepoints. This work performs a photometric analysis of relative irradianceexpected at the camera sensor as a result of intended operating conditionsand device specifications including laser power. The limiting effects of eye
safety compliance, minimum realizable shutter times and pixel bit depth forlinear response cameras are considered. Quantitative results are establisheddetermining dynamic range requirements on the camera, when exposurecontrol is needed, and when laser return can be expected to produce the
brightest pixels in the image.
Urban Scene Extraction from Mobile Ground
Based LiDAR Data
Joseph Lam1, Michael Greenspan1, Robin Harrap1, Kresimir Kusevic2, Paul Mrstik2
1QUEEN'SUNIVERSITY, CANADA, 2TERRAPOINTCANADA INC.
Efficient methods for extracting urban scene structures from 3D data isimportant when dealing with the high volume data collected from mobileterrestrial LiDAR. Rather than searching for primitive shapes directly in theraw 3D data, we demonstrate that the road can be used as a cue for
effectively localizing urban scene structures. Road extraction is done bydividing the road into many small sections, and Kalman filtering is then used
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Presented by Joseph Lam
May 20 (Thursday) - 10:15 - 11:15
to track changes of road parameters using a dynamic model. By limiting thesearch space along the extracted road and using dimensional constraints,near-road structures such as posts and power line are easily segmented in anefficient manner. The algorithm performs consistently well on many different
city scenes, with roads segmented accurately in an efficient manner andposts extracted even in the presence of other objects such as cars and trees.
3D Shape Retrieval and Recognition
Ridge Walking for 3D Surface Segmentation
Andrew Willis, Beibei Zhou
UNIVERSITYOFNORTHCAROLINAATCHARLOTTE, USA
This paper describes a new 3D surface segmentation algorithm thatseparates a closed surfaces into regions by computing surface contours thattraverse surface ridge structures. We refer to the approach as ridge-walkingsince these contours tend to follow convex ridge-like structures and/or
concave valley-like structures present within the geometry of the model.Segmentation is achieved by solving for closed ridge contours on thesurface, each of which serves to divide the surface into two disjoint regions.
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Presented by Andrew Willis
May 20 (Thursday) - 10:15 - 11:15
Results for three different segmentation approaches based on this approachare compared: (1) concave ridge walking, (2) convex ridge walking and (3)mixed concave/convex ridge walking. We also compare our results withother leading segmentation methods on standard data sets as well as new
datasets that provide important and interesting new challenges.
Conformal mapping-based 3D face recognition
Przemyslaw Szeptycki1, Mohsen Ardabilian1, Liming Chen1, Wei Zeng2, Davig Gu2, Dimitris Samaras2
1MI DEPARTMENT, LIRIS LABORATORY, ECOLECENTRALEDELYON, FRANCE, 2COMPUTERSCIENCE DEPARTMENT, STONYBROOKUNIVERSITY, USA
In this paper we present a conformal mapping-based approach for 3D facerecognition. The proposed approach makes use of conformal UVparameterization for mapping purpose and Shape Index decomposition forsimilarity measurement. Indeed, according to conformal geometry theory,
each 3D surface with disk topology can be mapped onto a 2D domainthrough a global optimization, resulting in a diffeomorphism, i.e.,
one-to-one and onto. This allows us to reduce the 3D surface matchingproblem to a 2D image matching one by comparing the corresponding 2D
conformal geometric maps. To deal with facial expressions, the Mobiustransformation of UV conformal space has been used to 'compress' facemimic region. Rasterized images are used as an input for (2D)2PCArecognition algorithm.
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Presented by Przemyslaw Szeptycki
May 20 (Thursday) - 10:15 - 11:15ICP Fusion Techniques for 3D Face Recognition
Robert McKeon, Patrick Flynn
UNIVERSITYOFNOTREDAME, USA
The 3D shape of the face has been shown to be a viable and robust biometric for security
applications. Many state of the art techniques use Iterative Closest Point (ICP) for 3D facematching. We propose and explore several optimizations of the ICP-based matching techniquerelating to the processing of multiple regions and the fusion of region matching scoresobtained from ICP alignment. The optimizations explored included: (i) the symmetric use of
probe and gallery face regions as ICP s model and data shapes, enabling score fusion; (ii)gallery and probe region matching score normalization; (iii) region selection based on facedata centroid rather than the nose tip, and (iv) region weighting. As a result of theseoptimizations, the rank-one recognition rate for a canonical matching experiment improved
from 96.4% to 98.6%, and the True Accept Rate (TAR) at 0.1% False Accept Rate (FAR)
improved from 90.4% to 98.5%.
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Presented by Robert McKeon
May 20 (Thursday) - 10:15 - 11:15
Medical Imaging and Augmented Reality
Indoor Localization Algorithms for a Human-
Operated Backpack System
George Chen, John Kua, Stephen Shum, Nikhil Naikal, Matthew Carlberg, Avideh Zakhor
UC BERKELEYVIDEOANDIMAGEPROCESSINGLAB, USA
Automated 3D modeling of building interiors is useful in applications such asvirtual reality and entertainment. Using a human-operated backpack system
equipped with 2D laser scanners and inertial measurement units, we developfour scan-matching-based algorithms to localize the backpack and comparetheir performance and tradeoffs. We present results for two datasets of a
30-meter-long indoor hallway and compare one of the best performinglocalization algorithms with a visual-odometry-based method. We find thatour scan-matching-based approach results in comparable or higheraccuracy.
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Presented by Avideh Zakhor
May 20 (Thursday) - 10:15 - 11:15Virtu4D: a Real-time Virtualization of Reality
Mourad Boufarguine1, Malek Baklouti1, Frederic Precioso2, Vincent Guitteny1
1THALESSECURITY SOLUTIONSANDSERVICES- RESEARCHDEPARTEMENT, FRANCE, 2ETIS ENSEA/CNRS/UNIV. CERGY-PONTOISE, FRANCE
In video surveillance systems, when dealing with dynamic complex scenes,
processing the information coming from multiple cameras and fusing theminto a comprehensible environment is a challenging task. This work
addresses the issue of providing a global and reliable representation of themonitored environment aiming at enhancing the perception and minimizingthe operator's effort. The proposed system Virtu4D is based on 3Dcomputer vision and virtual reality techniques and takes benefit from both
the "real" and the "virtual" worlds offering a unique perception of the scene.This paper presents a short overview of the framework along with thedifferent components of the design space: Video Model Layout, VideoProcessing and Immersive Model Generation. The final interface gathers the
2D information in the 3D context but also offers a complete 3D
representation of the dynamic environment allowing a free intuitive 3Dnavigation.
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Presented by Mourad Boufarguine
May 20 (Thursday) - 10:15 - 11:15Sparse Parallel Electronic Bowel Cleansing in CT
Colonography
Richard Boyes, Xujiong Ye, Gareth Beddoe, Greg Slabaugh
MEDICSIGHTPLC, UNITEDKINGDOM
We present a technique for storing the sparse data that often occurs whenprocessing three dimensional medical images. The technique uses raster scan
order to store the one dimensional volume indexes of each pixel location,and stores an inverted copy of these indexes for fast lookup. The invertedindex is stored as a Judy array which is shown to be highly efficient in lookuptimes while using very little memory compared to hash tables. We
demonstrate the efficiency of the data structure by performing partialvolume segmentation and digital removal of oral contrast agent within CTColonography (CTC).
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Presented by Xujiong Ye
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