21,664 research outputs found
Partial Order Reduction for Security Protocols
Security protocols are concurrent processes that communicate using
cryptography with the aim of achieving various security properties. Recent work
on their formal verification has brought procedures and tools for deciding
trace equivalence properties (e.g., anonymity, unlinkability, vote secrecy) for
a bounded number of sessions. However, these procedures are based on a naive
symbolic exploration of all traces of the considered processes which,
unsurprisingly, greatly limits the scalability and practical impact of the
verification tools.
In this paper, we overcome this difficulty by developing partial order
reduction techniques for the verification of security protocols. We provide
reduced transition systems that optimally eliminate redundant traces, and which
are adequate for model-checking trace equivalence properties of protocols by
means of symbolic execution. We have implemented our reductions in the tool
Apte, and demonstrated that it achieves the expected speedup on various
protocols
Active skeleton for bacteria modeling
The investigation of spatio-temporal dynamics of bacterial cells and their
molecular components requires automated image analysis tools to track cell
shape properties and molecular component locations inside the cells. In the
study of bacteria aging, the molecular components of interest are protein
aggregates accumulated near bacteria boundaries. This particular location makes
very ambiguous the correspondence between aggregates and cells, since computing
accurately bacteria boundaries in phase-contrast time-lapse imaging is a
challenging task. This paper proposes an active skeleton formulation for
bacteria modeling which provides several advantages: an easy computation of
shape properties (perimeter, length, thickness, orientation), an improved
boundary accuracy in noisy images, and a natural bacteria-centered coordinate
system that permits the intrinsic location of molecular components inside the
cell. Starting from an initial skeleton estimate, the medial axis of the
bacterium is obtained by minimizing an energy function which incorporates
bacteria shape constraints. Experimental results on biological images and
comparative evaluation of the performances validate the proposed approach for
modeling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the
proposed method can be found online at http://fluobactracker.inrialpes.fr.Comment: Published in Computer Methods in Biomechanics and Biomedical
Engineering: Imaging and Visualizationto appear i
A model-based approach to recovering the structure of a plant from images
We present a method for recovering the structure of a plant directly from a
small set of widely-spaced images. Structure recovery is more complex than
shape estimation, but the resulting structure estimate is more closely related
to phenotype than is a 3D geometric model. The method we propose is applicable
to a wide variety of plants, but is demonstrated on wheat. Wheat is made up of
thin elements with few identifiable features, making it difficult to analyse
using standard feature matching techniques. Our method instead analyses the
structure of plants using only their silhouettes. We employ a generate-and-test
method, using a database of manually modelled leaves and a model for their
composition to synthesise plausible plant structures which are evaluated
against the images. The method is capable of efficiently recovering accurate
estimates of plant structure in a wide variety of imaging scenarios, with no
manual intervention
Skeletons of stable maps II: Superabundant geometries
We implement new techniques involving Artin fans to study the realizability
of tropical stable maps in superabundant combinatorial types. Our approach is
to understand the skeleton of a fundamental object in logarithmic
Gromov--Witten theory -- the stack of prestable maps to the Artin fan. This is
used to examine the structure of the locus of realizable tropical curves and
derive 3 principal consequences. First, we prove a realizability theorem for
limits of families of tropical stable maps. Second, we extend the sufficiency
of Speyer's well-spacedness condition to the case of curves with good
reduction. Finally, we demonstrate the existence of liftable genus 1
superabundant tropical curves that violate the well-spacedness condition.Comment: 17 pages, 1 figure. v2 fixes a minor gap in the proof of Theorem D
and adds details to the construction of the skeleton of a toroidal Artin
stack. Minor clarifications throughout. To appear in Research in the
Mathematical Science
Unsupervised 3D Pose Estimation with Geometric Self-Supervision
We present an unsupervised learning approach to recover 3D human pose from 2D
skeletal joints extracted from a single image. Our method does not require any
multi-view image data, 3D skeletons, correspondences between 2D-3D points, or
use previously learned 3D priors during training. A lifting network accepts 2D
landmarks as inputs and generates a corresponding 3D skeleton estimate. During
training, the recovered 3D skeleton is reprojected on random camera viewpoints
to generate new "synthetic" 2D poses. By lifting the synthetic 2D poses back to
3D and re-projecting them in the original camera view, we can define
self-consistency loss both in 3D and in 2D. The training can thus be self
supervised by exploiting the geometric self-consistency of the
lift-reproject-lift process. We show that self-consistency alone is not
sufficient to generate realistic skeletons, however adding a 2D pose
discriminator enables the lifter to output valid 3D poses. Additionally, to
learn from 2D poses "in the wild", we train an unsupervised 2D domain adapter
network to allow for an expansion of 2D data. This improves results and
demonstrates the usefulness of 2D pose data for unsupervised 3D lifting.
Results on Human3.6M dataset for 3D human pose estimation demonstrate that our
approach improves upon the previous unsupervised methods by 30% and outperforms
many weakly supervised approaches that explicitly use 3D data
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