93,502 research outputs found

    Further improving geometric fitting

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    We give a formal definition of geometric fitting in a way that suits computer vision applications. We point out that the performance of geometric fitting should be evaluated in the limit of small noise rather than in the limit of a large number of data as recommended in the statistical literature. Taking the KCR lower bound as an optimality requirement and focusing on the linearized constraint case, we compare the accuracy of Kanatani's renormalization with maximum likelihood (ML) approaches including the FNS of Chojnacki et al. and the HEIV of Leedan and Meer. Our analysis reveals the existence of a method superior to all these. </p

    Cumulative object categorization in clutter

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    In this paper we present an approach based on scene- or part-graphs for geometrically categorizing touching and occluded objects. We use additive RGBD feature descriptors and hashing of graph configuration parameters for describing the spatial arrangement of constituent parts. The presented experiments quantify that this method outperforms our earlier part-voting and sliding window classification. We evaluated our approach on cluttered scenes, and by using a 3D dataset containing over 15000 Kinect scans of over 100 objects which were grouped into general geometric categories. Additionally, color, geometric, and combined features were compared for categorization tasks

    Designing a template bank to observe compact binary coalescences in Advanced LIGO's second observing run

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    We describe the methodology and novel techniques used to construct a set of waveforms, or template bank, applicable to searches for compact binary coalescences in Advanced LIGO's second observing run. This template bank is suitable for observing systems composed of two neutron stars, two black holes, or a neutron star and a black hole. The Post-Newtonian formulation is used to model waveforms with total mass less than 4 MM_{\odot} and the most recent effective-one-body model, calibrated to numerical relativity to include the merger and ringdown, is used for total masses greater than 4 MM_{\odot}. The effects of spin precession, matter, orbital eccentricity and radiation modes beyond the quadrupole are neglected. In contrast to the template bank used to search for compact binary mergers in Advanced LIGO's first observing run, here we are including binary-black-hole systems with total mass up to several hundreds of solar masses, thereby improving the ability to observe such systems. We introduce a technique to vary the starting frequency of waveform filters so that our bank can simultaneously contain binary-neutron-star and high-mass binary-black hole waveforms. We also introduce a lower-bound on the filter waveform length, to exclude very short-duration, high-mass templates whose sensitivity is strongly reduced by the characteristics and performance of the interferometers.Comment: 10 pages, 8 figure

    A decision support system for demand and capacity modelling of an accident and emergency department

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    © 2019 Operational Research Society.Accident and emergency (A&E) departments in England have been struggling against severe capacity constraints. In addition, A&E demands have been increasing year on year. In this study, our aim was to develop a decision support system combining discrete event simulation and comparative forecasting techniques for the better management of the Princess Alexandra Hospital in England. We used the national hospital episodes statistics data-set including period April, 2009 – January, 2013. Two demand conditions are considered: the expected demand condition is based on A&E demands estimated by comparing forecasting methods, and the unexpected demand is based on the closure of a nearby A&E department due to budgeting constraints. We developed a discrete event simulation model to measure a number of key performance metrics. This paper presents a crucial study which will enable service managers and directors of hospitals to foresee their activities in future and form a strategic plan well in advance.Peer reviewe
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