Abstract book (pdf) - ICPR 2010

09:00-11:10, Paper WeAT8.14
Automatic Face Replacement in Video based on 2D Morphable Model
Min, Feng, WuHan Inst. of Tech.
Sang, Nong, Huazhong Univ. of Science and Tech.
Wang, Zhefu, Wuhan Inst. of Tech.
This paper presents an automatic face replacement approach in video based on 2D morphable model. Our approach includes
three main modules: face alignment, face morph, and face fusion. Given a source image and target video, the Active Shape
Models (ASM) is adopted to source image and target frames for face alignment. Then the source face shape is warped to
match the target face shape by a 2D morphable model. The color and lighting of source face are adjusted to keep consistent
with those of target face, and seamlessly blended in the target face. Our approach is fully automatic without user interference,
and generates natural and realistic results.
09:00-11:10, Paper WeAT8.15
3D Deformable Surfaces with Locally Self-Adjusting Parameters – a Robust Method to Determine Cell Nucleus Shapes
Keuper, Margret, Univ. of Freiburg
Schmidt, Thorsten, Univ. of Freiburg
Padeken, Jan, Max-Planck-Insitute of Immunobiology
Heun, Patrick, Max-Planck-Inst. of Immunobiology
Palme, Klaus, Univ. of Freiburg
Burkhardt, Hans, Univ. of Freiburg
Ronneberger, Olaf, Univ. of Freiburg
When using deformable models for the segmentation of biological data, the choice of the best weighting parameters for
the internal and external forces is crucial. Especially when dealing with 3D fluorescence microscopic data and cells within
dense tissue, object boundaries are sometimes not visible. In these cases, one weighting parameter set for the whole contour
is not desirable. We are presenting a method for the dynamic adjustment of the weighting parameters, that is only depending
on the underlying data and does not need any prior information. The method is especially apt to handle blurred, noisy, and
deficient data, as it is often the case in biological microscopy.
09:00-11:10, Paper WeAT8.16
Decomposition of Dynamic Textures using Morphological Component Analysis: A New Adaptative Strategy
Dubois, Sloven, Univ. de La Rochelle
Péteri, Renaud, Univ. of La Rochelle
Ménard, Michel, Univ. de La Rochelle
The research context of this work is dynamic texture analysis and characterization. Many dynamic textures can be modeled
as a large scale propagating wave and local oscillating phenomena. The Morphological Component Analysis algorithm is
used to retrieve these components using a well chosen dictionary. We define a new strategy for adaptive thresholding in
the Morphological Component Analysis framework, which greatly reduces the computation time when applied on videos.
Tests on synthetic and real image sequences illustrate the efficiency of the proposed method and future prospects are
finally exposed.
09:00-11:10, Paper WeAT8.17
Anisotropic Contour Completion for Cell Microinjection Targeting
Becattini, Gabriele, Italian Inst. of Tech.
Mattos, Leonardo, Italian Inst. of Tech.
Caldwell, Darwin G., Italian Inst. of Tech.
This paper shows a novel application of the diffusion tensor for anisotropic image processing. The designed system aims
at spotting and localizing injection points on a population of adherent cells lying on a Petri’s dish. The overall procedure
is described including pre-filtering, ridge enhancement, cell segmentation, shape analysis and injection point detection.
The anisotropic contour completion (ACC) employed is equivalent to a dilation with a continuous elliptic structural element
that takes into account the local orientation of the contours to be closed, preventing extension towards the normal direction.
Experiments carried out on real images from an optical microscope revealed a remarkable reliability with up to 86% of
cells in the field of view correctly segmented and targeted for microinjection.
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