O Workshop de Teses e Dissertações em Computação Gráfica, Processamento de Imagens e Visão
Computacional (WTDCGPI) visa criar um espaço para debate e divulgação dos trabalhos de doutorado
e mestrado desenvolvidos no país em Computação Gráfica, Processamento de Imagens, Visão
Computacional e Visualização. O evento tem sido parte integrante do SIBGRAPI – Simpósio
Brasileiro de Computação Gráfica e Processamento de Imagens, que em 2008 ocorre na cidade de
Campo Grande, MS, no período de 12 a 15 de outubro de 2008.
Foram aceitas submissões de trabalhos de alunos regularmente matriculados em cursos de doutorado ou
mestrado vinculados a cursos de Pós-Graduação stricto sensu no país, ou ainda ex-alunos que tenham
defendido tese ou dissertação depois de 01/01/2008 e antes do prazo final para submissão em
09/07/2008.
Como forma de permitir uma maior disseminação dos benefícios do Workshop aos autores, decidiu-se
por aceitar o maior número possível de trabalhos, respeitando os pareceres dos revisores (pelo menos 2
aceitações). Ao todo, foram aceitos 8 trabalhos na área de Computação Gráfica e 7 na área de
Processamento de Imagens e Visão Computacional de um total de 18 submetidos.
Os trabalhos aceitos na área de Computação Gráfica versam sobre temas variados tais como:
visualização e reconstrução a partir de modelos baseados em pontos, síntese de fontes de luz,
visualização volumétrica, deformação de imagens e simulação e animação baseada em física.
Os trabalhos aceitos na área de Processamento de Imagens e Visão Computacional também
contemplaram temas variados, incluindo a segmentação de imagens coloridas, realce de imagens,
biometria a partir de impressões digitais, processamento de imagens aéreas, médicas e biológicas, bem
como métodos para representação e análise de formas.
Claudio Esperança and
Herman Martins Gomes
WTDCGPI 2008 Co-Chairs.
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Accepted Work
Image Processing
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Discrete Models for Animating Gas-Liquid and Fluid-Surface Interactions
Sicilia F. Judice, Gilson A. Giraldi, National Laboratory of Scientific Computing
(pp 7 - 16).
(paper)
The past two decades showed a rapid growing of
physically-based modeling of fluids and solid for computer
graphics applications. In particular, techniques in the
field of Computational Mechanics have been applied for realistic
animation of systems that involve gas-fluid and
fluid-surface interaction for computer graphics and virtual
reality applications. The main goal of our work is the
development of a particle based framework to create realistic
animations of such systems. Specifically, we model
and simulate the gas through a Lattice Gas Cellular Automata
(LGCA), the liquid by Smoothed Particle Hydrodynamics
(SPH) method and the surface through Mass-Spring
systems. LGCAs are discrete models based on point particles
that move on a lattice, according to suitable rules in
order to mimic a fully molecular dynamics. SPH is a Lagrangian,
meshfree method for numerical simulation
which is based on particle systems and interpolation theory.
Mass-Spring systems may be geometrically represented
by regular meshes which nodes are treated like
mass points and each edge acts like a spring. When combining
these methods (LGCA, SPH and Mass-Spring), we
get the advantage of the low computational cost of cellular
automata and mass-spring systems and the realistic
fluid dynamics inherent in the SPH to develop a new animating
framework for computer graphics applications. In
this work, we discuss the theoretical elements of our proposal
and present some preliminary experimental results.
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Exploration of Volumetric Datasets through Interaction in Transfer Function Space
Francisco de M. Pinto, Carla M. D. S. Freitas, Instituto de Informática – Universidade Federal do Rio Grande do Sul
(pp 17 - 26).
(paper)
Direct volume rendering techniques allow
visualization of volume data without extracting
intermediate geometry. The mapping from voxel
attributes to optical properties is performed by transfer
functions which, consequently, play a crucial role in
building informative images from the data. Onedimensional
transfer functions, which are based only
on a scalar value per voxel, often do not provide
proper visualizations. On the other hand, multidimensional
transfer functions can perform more
sophisticated data classification, based on vectorial
voxel signatures. The transfer function design is a nontrivial
and unintuitive task, especially in the multidimensional
case, and its controlled modification
allows the user to selectively enhance different
structures in the volume. In this paper we discuss the
interactive approach of a transfer function design
technique that allows the user to explore volumetric
datasets by interacting with a derived space as well as
with voxels in the volume space.
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Fluid Warping
Dalia Bonilla, Luiz Velho, André Nachbin, Instituto de Matemática Pura e Aplicada Luis Gustavo Nonato, Universidade de São Paulo - São Carlos
(pp 27 - 32).
(paper)
Warping techniques can be complicated and difficult to
use, but through the use of fluid dynamics the warping becomes
simple and it is intuitively controlled by physical
properties such as viscosity and forces. These properties
are naturally associated with the image itself or with spatial
control handles. The key idea is to think of the image
domain as a two-dimensional incompressible and homogeneous
fluid, and to use the Navier Stokes equations
to change it by applying forces to the image function. In
this way, the process does not move the image values as
in fluid simulations, but transforms the coordinates of a
parametrization of the image through a vector field generated
by the simulation equations — effectively acting as a
texture mapping.
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Image-Based Techniques for Surface Reconstruction of Adaptively Sampled Models
Ricardo Marroquim, Universidade Federal do Rio de Janeiro Paulo Roma Cavalcanti, Universidade Federal do Rio de Janeiro
(pp 33 - 42).
(paper)
Image based methods have proved to efficiently render
scenes with a higher efficiency than geometry based approaches,
mainly because one of their most important advantages:
the bounded complexity by the image resolution,
instead of by the number of primitives. Furthermore, due
to their parallel and discrete nature, they are highly suitable
for GPU implementations. On the other hand, during
the last few years point-based graphics has emerged as a
promising complement to other representations. However,
with the continuous increase of scene complexity, solutions
for directly processing and rendering point clouds are in
demand. In this paper, algorithms for efficiently rendering
large point models using image reconstruction techniques
are proposed. Except for the projection of samples onto
screen space, the reconstruction time is bounded only by
the screen resolution. The method is also extended to interpolate
other primitives, such as lines and triangles. In addition,
no extra data-structure is required, making the strategy
memory efficient.
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Least Squares and Point-based Surfaces: New Perspectives and Applications
João Paulo Gois, Antonio Castelo Filho, Instituto de Ciências Matemáticas e de Computação Universidade de São Paulo
(pp 43 - 52).
(paper)
Surface approximation from unorganized points belongs
to the state-of-art of computer graphics. In this work,
we present approaches for surface reconstruction that
are based on efficient numerical schemes for function
approximation from scattered data and on sophisticate
data structures. In addition, we develop a relevant
surface reconstruction method to model moving interfaces,
specifically, interfaces of numerically simulated multiphase
fluid flow. Finally, from our accumulated experiences
on numerical schemes and on the development of surface
reconstruction methods, we propose a matrix-free approach
for rendering arbitrary volumetric scattered data, which
presents interesting properties to be implemented on GPU.
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Renderizações Não Fotorealísticas para Estilização de Imagens e Vídeos usando Areia Colorida
Laurindo S. Britto Neto, Departamento de Ciências da Natureza/Picos - UFPI
Bruno M. Carvalho (Orientador), Departamento de Informática e Matemática Aplicada - UFRN
(pp 53 - 62).
(paper)
Non-Photorealisitc Rendering (NPR) can be defined as
the processing of scenes, images or videos into artwork.
This work presents a new method of NPR for stylization of
images and videos, based on a typical artistic expression
of the Northeast region of Brazil, that uses colored sand
to compose landscape images on the inner surface of glass
bottles. This method is comprised by one technique for generating
2D procedural textures of sand, and two techniques
that mimic effects created by the artists using their tools.
We also present a method for generating 2 1/2D animations
of stylized videos as if they were placed in a sandbox. The
temporal coherence within these stylized videos can be enforced
on individual objects with the aid of a video segmentation
algorithm.
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Sistema Composto para Amostragem e Geração de Luzes a partir de Mapas de Iluminação
Aldo R. Zang, Laboratório VISGRAF - IMPA Luiz Velho, Laboratório VISGRAF - IMPA
(pp 63 - 68).
(paper)
In this paper we introduce a new approach to the problem
of direct illumination in physically-based rendering of
3D scenes using illumination maps captured from real environments.
We developed a system that takes advantage of
the best features of the current solutions to the problem: namely,
the approximation of illumination maps through directional
lights; and stochastic sampling of the light maps.
Our framework is flexible and can be used with most rendering
programs.
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Um sistema simplificado para animação física usando malhas tetraedrais
Guina Sotomayor Alzamora, Claudio Esperança, University Federal of Rio of Janeiro Computer Graphics Laboratory
(pp 69 - 78).
(paper)
We present a simplified approach for animation of geometrically
complex deformable objects represented as tetrahedral
meshes. Our prototype system detects and responds
to collisions of objects subject to elastic deformations
of variable stiffness. The proposed approach combines
several techniques, namely, collision detection using a Spatial
Hashing, collision response through a contact surface
that use a consistent penetration depth using propagation,
an estimate for displacement vector of the deformation region
and binary search to separate objects. The dynamics
is based on shape matching and a modal analysis scheme,
using an Euler explicit-implicit integrator. Preliminary results
show that collisions between objects containing several
hundreds tetrahedra can be animated in real-time.
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Image Processing and Computer Vision
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Automatização do Ajuste de Segmentadores Neurais de Imagens Coloridas
Fernando H. B. Cardoso, Herman M. Gomes, UFCG, Departamento de Sistemas e Computação - Laboratório de Visão Computacional
(pp 80 - 85).
(paper)
Tuning material-detecting-capable image segmenters is
performed manually, with little automation. Once the segmentation
is usually an intermediary step to a myriad of applications
within Computer Vision, the lack of automation
leads to effort wasting in secondary tasks. In this work, we
propose a techinique to automatically tune neural networks
that segment images based on color and texture information.
This technique does not require human supervision,
reducing the effort in obtaining segmenters. The automatically
tuned neural networks detect 2.56% more of the material’s
surface – related to other segmenters also tested –
with false acceptance rate of 6.89%.
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Contrast Enhancement in Digital Imaging using Histogram Equalization
David Menotti, Universidade Federal de Ouro Preto
Arnaldo de A. Araújo, Gisele L. Pappa, Universidade Federal de Minas Gerais
Laurent Najman, Université Paris-Est
Jacques Facon, Pontifícia Universidade Católica do Paraná
(pp 86 - 95).
(paper)
This work proposes two methodologies for fast image
contrast enhancement based on histogram equalization
(HE), one for gray-level images, and other for
color images. For gray-level images, we propose a technique
called Multi-HE, which decomposes the input image
into several sub-images, and then applies the classical
HE process to each one of them. In order to decompose
the input image, we propose two different discrepancy
functions, conceiving two new methods. Experimental results
show that both methods are better in preserving
the brightness and producing more natural looking images
than other HE methods. For color images, we
introduce a generic fast hue-preserving histogram equalization
method based on the RGB color space, and
two instantiations of the proposed generic method, using
1D and 2D histograms. HE is performed using shift
hue-preserving transformations, avoiding the appearance
of unrealistic colors. Experimental results show that
the value of the image contrast produced by our methods
is in average 50% greater than the value of contrast
in the original image, still keeping the quality of the output
images close to the original.
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Fusão de Métodos Baseados em Minúcias e em Cristas para Reconhecimento de Impressões Digitais
Fernanda Pereira Sartori Falguera, Aparecido Nilceu Marana, UNESP
(pp 96 - 105).
(paper)
Biometrics is one of the major tendencies in human
identification and fingerprints are the most widely
used biometrics trait. However, considering the
automatic fingerprint recognition a completely solved
problem is a common mistake. The most extensively
used methods, the minutiae-based methods, do not
perform well on poor-quality images and when just a
small area of overlap between the template and the
query image exists. The Multibiometrics is considered
one of the keys to overcome the weakness and to
improve the accuracy of biometrics systems. This
master thesis presents the fusion of minutiae-based
and ridge-based methods. The achieved results (mean
reduction of the Equal Error Rate of more than 30%
and an increase of 75% in the Correct Retrieval Rate)
have showed that the fusion of minutiae-based and
ridge-based methods can provide a significant
accuracy improvement of the fingerprint recognition
systems.
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High-resolution image resonstruction using the Discontinuity Adaptive ICM algorithm
MARTINS, A.L.D. and MASCARENHAS, N.D.A., Universidade Federal de São Carlos
(pp 106 - 115).
(paper)
Super-Resolution reconstruction methods intend to reconstruct
a high-resolution image from a set of lowresolution
observations. For that, the observed images must
have sub-pixel displacements between each other. This requirement
allows the existence of different information
on each of the low-resolution images. This paper discusses
a Bayesian approach for the super-resolution reconstruction
problem using Markov Random Fields (MRF)
and the Potts-Strauss model for the image characterization.
Since it is difficult to maximize the joint probability,
the Iterated Conditional Modes (ICM) algorithm is
used to maximize the local conditional probabilities sequentially.
For the oversmoothness inherent to Maximum
a Posteriori (MAP) formulations using MRF prior models,
we adopt a discontinuity adaptive (DA) procedure
for the ICM algorithm. The proposed method was evaluated
in a simulated situation by the Peak signal-to-noise
ratio (PSNR) method and the Universal Image Quality Index
(UIQI). Also, video frames with sub-pixel displacements
were used for the visual evaluation. The results
indicate the effectiveness of our approach both by numerical
and visual evaluation.
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Mapeamento e Monitoramento Ambiental Usando Imagens Aéreas de Pequeno Formato
Natal Henrique Cordeiro, Bruno Motta de Carvalho, Luiz Marcos Garcia Gonçalves, Universidade Federal do Rio Grande do Norte
(pp 116 - 125).
(paper)
We propose a technique that uses small format aerial
images, or SFAI, considered as not controlled, and stereophotogrammetry
techniques to construct georeferenced mosaics.
Images are obtained using a simple digital camera
coupled to a radio controlled (RC) helicopter. Techniques
for removing common distortions are applied and the relative
orientation of the models are recovered using perspective
geometry. Ground truth points are used to get absolute
orientation, plus a definition of scale and a coordinate system
which relates image measures to the ground. The mosaic
is read into a GIS system, providing useful information
to different types of users, such as researchers, government
officers, fishers and tourism enterprises. Results are
reported, illustrating the applicability of the system. The
main contribution is the generation of georeferenced mosaics
using SFAIs, what has not been widely explored previously
in cartography projects. The proposed architecture
presents a viable and much less expensive solution, when
compared to systems using controlled pictures.
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Reconhecimento Semi-Automático de Sinus Frontais para Identificação Humana Forense Baseado na Transformada Imagem-Floresta e no Contexto da Forma
Juan Rogelio Falguera, Aparecido Nilceu Marana - UNESP
(pp 126 - 135).
(paper)
Several methods based on Biometrics such as
fingerprint, face and iris have been proposed for
person identification. However, for postmortem
identification such biometric measurements may not be
available. In such cases, parts of the human skeleton
can be used. Previous investigations showed that
frontal sinus patterns are unique for each individual.
The objective of this master thesis is to propose a
computational method for frontal sinus recognition for
postmortem human identification. In order to achieve
this, methods for frontal sinus segmentation from
anteroposterior radiographs were evaluated. The
method based on Image-Foresting Transform has
shown itself efficient in frontal sinus segmentation from
radiograph images. Techniques for extracting frontal
sinus geometrical and shape-based descriptors were
investigated and implemented as well. The results
obtained in our experiments confirm the outcomes
described in literature about the individuality of the
frontal sinus and its feasibility in terms of precision
and usability for postmortem human identification.
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Shape Descriptors based on Tensor Scale
Fernanda A. Andaló, Ricardo da S. Torres, Alexandre X. Falcão, Institute of Computing – State University of Campinas (Unicamp)
(pp 136 - 144).
(paper)
Tensor scale is a morphometric parameter that unifies
the representation of local structure thickness, orientation,
and anisotropy, which can be used in several computer vision
and image processing tasks. We exploit this concept for
binary images and propose two shape descriptors – Tensor
Scale Descriptor with Influence Zones and Tensor Scale
Contour Saliences. It also introduces a robust method to
compute tensor scale, using a graph-based approach – the
image foresting transform. Experimental results are provided,
showing the effectiveness of the proposed methods,
when compared to other relevant methods with regard to
their use in content-based image retrieval tasks.
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Program Committee
Workshop Co-Chairs: |
Claudio Esperança (UFRJ) and Herman Martins Gomes (UFCG)
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Carlos Morimoto, USP
Claudio Esperanca, UFRJ
Esteban Clua, UFF
Herman Martins Gomes, UFCG
Joao Marques de Carvalho, UFCG
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João Comba, UFRGS
Luiz Henrique de Figueiredo, IMPA
Nelson Mascarenhas, UFSCar
Olga Bellon, UFPR
Waldemar Celes, PUC-Rio
Wu Shin-Ting, UNICAMP
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Reviewers
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Arnaldo de Albuquerque, UFMG
Carlos Morimoto, USP
Chauã Queirolo, UFPR
Claudio Esperanca, UFRJ
Esteban Clua, UFF
Harlen Batagelo, UNICAMP
Herman Martins Gomes, UFCG
Joao Carvalho, UFCG
João Comba, UFRGS
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Julio d'Alge, INPE
Junior Barrera, USP
Luciano Silva, UFPR
Luiz Henrique de Figueiredo, IMPA
Murillo Homem, UFSCar
Nelson Mascarenhas, UFSCar
Olga Bellon, UFPR
Waldemar Celes, PUC-Rio
Wu Shin-Ting, UNICAMP
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