51,188 research outputs found
Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition
This paper presents a robust and dynamic face recognition technique based on
the extraction and matching of devised probabilistic graphs drawn on SIFT
features related to independent face areas. The face matching strategy is based
on matching individual salient facial graph characterized by SIFT features as
connected to facial landmarks such as the eyes and the mouth. In order to
reduce the face matching errors, the Dempster-Shafer decision theory is applied
to fuse the individual matching scores obtained from each pair of salient
facial features. The proposed algorithm is evaluated with the ORL and the IITK
face databases. The experimental results demonstrate the effectiveness and
potential of the proposed face recognition technique also in case of partially
occluded faces.Comment: 8 pages, 2 figure
Recycling BiCGSTAB with an Application to Parametric Model Order Reduction
Krylov subspace recycling is a process for accelerating the convergence of
sequences of linear systems. Based on this technique, the recycling BiCG
algorithm has been developed recently. Here, we now generalize and extend this
recycling theory to BiCGSTAB. Recycling BiCG focuses on efficiently solving
sequences of dual linear systems, while the focus here is on efficiently
solving sequences of single linear systems (assuming non-symmetric matrices for
both recycling BiCG and recycling BiCGSTAB).
As compared with other methods for solving sequences of single linear systems
with non-symmetric matrices (e.g., recycling variants of GMRES), BiCG based
recycling algorithms, like recycling BiCGSTAB, have the advantage that they
involve a short-term recurrence, and hence, do not suffer from storage issues
and are also cheaper with respect to the orthogonalizations.
We modify the BiCGSTAB algorithm to use a recycle space, which is built from
left and right approximate invariant subspaces. Using our algorithm for a
parametric model order reduction example gives good results. We show about 40%
savings in the number of matrix-vector products and about 35% savings in
runtime.Comment: 18 pages, 5 figures, Extended version of Max Planck Institute report
(MPIMD/13-21
Random Filters for Compressive Sampling and Reconstruction
We propose and study a new technique for efficiently acquiring and reconstructing signals based on convolution with a fixed FIR filter having random taps. The method is designed for sparse and compressible signals, i.e., ones that are well approximated by a short linear combination of vectors from an orthonormal basis. Signal reconstruction involves a non-linear Orthogonal Matching Pursuit algorithm that we implement efficiently by exploiting the nonadaptive, time-invariant structure of the measurement process. While simpler and more efficient than other random acquisition techniques like Compressed Sensing, random filtering is sufficiently generic to summarize many types of compressible signals and generalizes to streaming and continuous-time signals. Extensive numerical experiments demonstrate its efficacy for acquiring and reconstructing signals sparse in the time, frequency, and wavelet domains, as well as piecewise smooth signals and Poisson processes
Finding Safety in Numbers with Secure Allegation Escrows
For fear of retribution, the victim of a crime may be willing to report it
only if other victims of the same perpetrator also step forward. Common
examples include 1) identifying oneself as the victim of sexual harassment,
especially by a person in a position of authority or 2) accusing an influential
politician, an authoritarian government, or ones own employer of corruption. To
handle such situations, legal literature has proposed the concept of an
allegation escrow: a neutral third-party that collects allegations anonymously,
matches them against each other, and de-anonymizes allegers only after
de-anonymity thresholds (in terms of number of co-allegers), pre-specified by
the allegers, are reached.
An allegation escrow can be realized as a single trusted third party;
however, this party must be trusted to keep the identity of the alleger and
content of the allegation private. To address this problem, this paper
introduces Secure Allegation Escrows (SAE, pronounced "say"). A SAE is a group
of parties with independent interests and motives, acting jointly as an escrow
for collecting allegations from individuals, matching the allegations, and
de-anonymizing the allegations when designated thresholds are reached. By
design, SAEs provide a very strong property: No less than a majority of parties
constituting a SAE can de-anonymize or disclose the content of an allegation
without a sufficient number of matching allegations (even in collusion with any
number of other allegers). Once a sufficient number of matching allegations
exist, the join escrow discloses the allegation with the allegers' identities.
We describe how SAEs can be constructed using a novel authentication protocol
and a novel allegation matching and bucketing algorithm, provide formal proofs
of the security of our constructions, and evaluate a prototype implementation,
demonstrating feasibility in practice.Comment: To appear in NDSS 2020. New version includes improvements to writing
and proof. The protocol is unchange
Estimating Jones and HOMFLY polynomials with One Clean Qubit
The Jones and HOMFLY polynomials are link invariants with close connections
to quantum computing. It was recently shown that finding a certain
approximation to the Jones polynomial of the trace closure of a braid at the
fifth root of unity is a complete problem for the one clean qubit complexity
class. This is the class of problems solvable in polynomial time on a quantum
computer acting on an initial state in which one qubit is pure and the rest are
maximally mixed. Here we generalize this result by showing that one clean qubit
computers can efficiently approximate the Jones and single-variable HOMFLY
polynomials of the trace closure of a braid at any root of unity.Comment: 22 pages, 11 figures, revised in response to referee comment
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