High-quality real-time temporal segmentation tool for video editing software

The increasing use of video editing software has resulted in a necessity for faster and more efficient editing tools. Here, we propose a lightweight high-quality video indexing tool that is suitable for video editing software.

NAMA3DS1-COSPAD1: Subjective video quality assessment database on coding conditions introducing freely available high quality 3D stereoscopic sequences

Research in stereoscopic 3D coding, transmission and subjective assessment methodology depends largely on the availability of source content that can be used in cross-lab evaluations. While several studies have already been presented using proprietary content, comparisons between the studies are difficult since discrepant contents are used. Therefore in this paper, a freely available dataset of high quality Full-HD stereoscopic sequences shot with a semiprofessional 3D camera is introduced in detail. The content was designed to be suited for usage in a wide variety of applications, including high quality studies. A set of depth maps was calculated from the stereoscopic pair. As an application example, a subjective assessment has been performed using coding and spatial degradations. The Absolute Category Rating with Hidden Reference method was used. The observers were instructed to vote on video quality only. Results of this experiment are also freely available and will be presented in this paper as a first step towards objective video quality measurement for 3DTV.

Temporal segmentation tool for high-quality real time video editing software

The increasing use of video editing software requires faster and more efficient editing tools. As a first step, these tools perform a temporal segmentation in shots that allows a later building of indexes describing the video content. Here, we propose a novel real-time high-quality shot detection strategy, suitable for the last generation of video editing software requiring both low computational cost and high quality results. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that helps to detect and discard false detections. This motion analysis is carried out exclusively over a reduced set of candidate transitions, thus maintaining the computational requirements demanded by new applications to fulfill user needs.

High-quality conforming hexahedral meshes of patient-specific abdominal aortic aneurysms including their intraluminal thrombi

In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.

High-quality region-based foreground segmentation using a spatial grid of SVM classifiers

This paper presents a novel background modeling system that uses a spatial grid of Support Vector Machines classifiers for segmenting moving objects, which is a key step in many video-based consumer applications. The system is able to adapt to a large range of dynamic background situations since no parametric model or statistical distribution are assumed. This is achieved by using a different classifier per image region that learns the specific appearance of that scene region and its variations (illumination changes, dynamic backgrounds, etc.). The proposed system has been tested with a recent public database, outperforming other state-of-the-art algorithms.

3LD: towards high quality, industry-ready linguistic Linked Licensed Data

The application of Linked Data technology to the publication of linguistic data promises to facilitate interoperability of these data and has lead to the emergence of the so called Linguistic Linked Data Cloud (LLD) in which linguistic data is published following the Linked Data principles. Three essential issues need to be addressed for such data to be easily exploitable by language technologies: i) appropriate machine-readable licensing information is needed for each dataset, ii) minimum quality standards for Linguistic Linked Data need to be defined, and iii) appropriate vocabularies for publishing Linguistic Linked Data resources are needed. We propose the notion of Licensed Linguistic Linked Data (3LD) in which different licensing models might co-exist, from totally open to more restrictive licenses through to completely closed datasets.

Building from building waste: The development of an instrument to determine the circularity of materials from the existing building stock in order to maximise high quality reuse

On a global level the population growth and increase of the middle class lead to a growing demand on material resources. The built environment has an enormous impact on this scarcity. In addition, a surplus of construction and demolition waste is a common problem. The construction industry claims to recycle 95% of this waste but this is in fact mainly downcycling. Towards the circular economy, the quality of reuse becomes of increasing importance. Buildings are material warehouses that can contribute to this high quality reuse. However, several aspects to achieve this are unknown and a need for more insight into the potential for high quality reuse of building materials exists. Therefore an instrument has been developed that determines the circularity of construction waste in order to maximise high quality reuse. The instrument is based on three principles: ‘product and material flows in the end of life phase’, ‘future value of secondary materials and products’ and ‘the success of repetition in a new life cycle’. These principles are further divided into a number of criteria to which values and weighting factors are assigned. A degree of circularity can then be determined as a percentage. A case study for a typical 70s building is carried out. For concrete, the circularity is increased from 25% to 50% by mapping out the potential for high quality reuse. During the development of the instrument it was clarified that some criteria are difficult to measure. Accurate and reliable data are limited and assumptions had to be made. To increase the reliability of the instrument, experts have reviewed the instrument several times. In the long-term, the instrument can be used as a tool for quantitative research to reduce the amount of construction and demolition waste and contribute to the reduction of raw material scarcity.

Building a high-quality workforce : the Federal Career Intern Program /

"A report to the President and the Congress of the United States by the U.S. Merit Systems Protection Board."

Binghamton wastewater management study : report of the U.S. Fish and Wildlife Service on plans developed by the U.S. Army Corps of Engineers for short- and long-range wastewater management to insure high quality water for future generations in Broome and Tioga Counties.

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