1,526 research outputs found
Appellate Settlement Conference Programs: A Case Study
The 1990s may be the decade in which the courts bring alternative dispute resolution in house. Professor Owen Fiss\u27 nightmare that private settlement will rob courts of cases for the dispensation of justice and the furtherance of societal goals3 has become Professor Carrie Menkel-Meadow\u27s foreboding that the courts will co-opt and drain the life from true alternative dispute resolution (ADR) processes.4 It may be argued that appellate court-sponsored settlement programs dodge both of these criticisms because parties have had a day in court, the process is a form of mediation, and the settlement is thus final only if the parties agree to settle and because appellate settlement programs may in fact provide a much-needed education for attorneys about the workings and benefits of ADR
Projective Bundle Adjustment from Arbitrary Initialization Using the Variable Projection Method
Bundle adjustment is used in structure-from-motion pipelines as final refinement stage requiring a sufficiently good initialization to reach a useful local mininum. Starting from an arbitrary initialization almost always gets trapped in a poor minimum. In this work we aim to obtain an initialization-free approach which returns global minima from a large proportion of purely random starting points. Our key inspiration lies in the success of the Variable Projection (VarPro) method for affine factorization problems, which have close to 100% chance of reaching a global minimum from random initialization. We find empirically that this desirable behaviour does not directly carry over to the projective case, and we consequently design and evaluate strategies to overcome this limitation. Also, by unifying the affine and the projective camera settings, we obtain numerically better conditioned reformulations of original bundle adjustment algorithms
Robust tracking for augmented reality
In this paper a method for improving a tracking algorithm in an augmented
reality application is presented. This method addresses several issues to this
particular application, like marker-less tracking and color constancy with low
quality cameras, or precise tracking with real-time constraints. Due to size restrictions
some of the objects are tracked using color information. To improve the
quality of the detection, a color selection scheme is proposed to increase color
distance between different objects in the scene. Moreover, a new color constancy
method based in a diagonal-offset model and k-means is presented. Finally, some
real images are used to show the improvement with this new method.Universidad de Málaga, Campus de Excelencia Internacional AndalucĂa Tech. Ministry of Education of Spain (TIN2013-42253P), Junta de AndalucĂa of Spain (TIC-1692
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Projective Bundle Adjustment from Arbitrary Initialization Using the Variable Projection Method
Bundle adjustment is used in structure-from-motion pipelines as final refinement stage requiring a sufficiently good initialization to reach a useful local mininum. Starting from an arbitrary initialization almost always gets trapped in a poor minimum. In this work we aim to obtain an initialization-free approach which returns global minima from a large proportion of purely random starting points. Our key inspiration lies in the success of the Variable Projection (VarPro) method for affine factorization problems, which have close to 100% chance of reaching a global minimum from random initialization. We find empirically that this desirable behaviour does not directly carry over to the projective case, and we consequently design and evaluate strategies to overcome this limitation. Also, by unifying the affine and the projective camera settings, we obtain numerically better conditioned reformulations of original bundle adjustment algorithms
Assessment of the Harmonic Balance Method for Rotor Blade Performance Predictions
This paper presents an assessment of the harmonic balance method for rotor blade performance predictions. The
harmonic balance method within the HMB3 solver of Glasgow University has been extended to the use with overset
grids, and results are presented for the PSP and AH-64A rotor blades in hover and forward flight. The predictions
are compared with results from steady-state and time marching simulations. In particular, the harmonic balance
method is assessed for capturing key flow features, such as the strength of the advancing blade shockwave and
retreating side blade dynamic stall. The limitations of the method are also discussed. The findings show that the
harmonic balance method is a promising alternative to time-marching simulations due to a significant reduction in
computational costs, leading to the potential use of high-fidelity Navier-Stokes methods in optimisation studies
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Creatures Great and SMAL: Recovering the Shape and Motion of Animals from Video
We present a system to recover the 3D shape and motion of a wide variety of
quadrupeds from video. The system comprises a machine learning front-end which
predicts candidate 2D joint positions, a discrete optimization which finds
kinematically plausible joint correspondences, and an energy minimization stage
which fits a detailed 3D model to the image. In order to overcome the limited
availability of motion capture training data from animals, and the difficulty
of generating realistic synthetic training images, the system is designed to
work on silhouette data. The joint candidate predictor is trained on
synthetically generated silhouette images, and at test time, deep learning
methods or standard video segmentation tools are used to extract silhouettes
from real data. The system is tested on animal videos from several species, and
shows accurate reconstructions of 3D shape and pose.GlaxoSmithKlin
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