521 research outputs found

    A color-based objective quality metric for point cloud contents

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    In recent years, point clouds have gained popularity as a promising representation for volumetric contents in immersive scenarios. Standardization bodies such as MPEG have been developing new compression standards for point cloud contents to reduce the volume of data, while maintaining an acceptable level of visual quality. To do so, reliable metrics are needed in order to automatically estimate the perceptual quality of degraded point cloud contents. Whereas several objective metrics have been developed to assess the geometrical impairment of degraded point cloud contents, fewer publications have been devoted to evaluating color artifacts.In this paper, we propose new color-based objective metrics for quality evaluation of point cloud contents. Our work extracts color statistics from both reference and degraded point cloud contents, in order to assess the level of impairment. Using publicly available ground-truth data, we compare the performance of our proposed work with state-of-the-art metrics, and we demonstrate how the color metrics are able to achieve comparable results with respect to widely adopted solutions. Moreover, we combine color- and geometry-based metrics in order to provide a global quality score. The novelty of our works resides in simultaneously taking both degradation types into account, while being independent of the rendering process. Results show that our solution is able to overcome the limitations of focusing on only one type of degradation, achieving better performance with respect to current metrics

    Improving the Boosted Correlogram

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    Introduced seven years ago, the correlogram is a simple statistical image descriptor that nevertheless performs strongly on image retrieval tasks. As a result it has found wide use as a component inside larger systems for content-based image and video retrieval. Yet few studies have examined potential variants of the correlogram or compared their performance to the original. This paper presents systematic experiments on the correlogram and several variants under different conditions, showing that the results may vary significantly depending on both the variant chosen and its mode of application. As expected, the experimental setup combining correlogram variants with boosting shows the best results of those tested. Under these prime conditions, a novel variant of the correlogram shows a higher average precision for many image categories than the form commonly used

    A Method Of Content-based Image Retrieval For The Generation Of Image Mosaics

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    An image mosaic is an artistic work that uses a number of smaller images creatively combined together to form another larger image. Each building block image, or tessera, has its own distinctive and meaningful content, but when viewed from a distance the tesserae come together to form an aesthetically pleasing montage. This work presents the design and implementation of MosaiX, a computer software system that generates these image mosaics automatically. To control the image mosaic creation process, several parameters are used within the system. Each parameter affects the overall mosaic quality, as well as required processing time, in its own unique way. A detailed analysis is performed to evaluate each parameter individually. Additionally, this work proposes two novel ways by which to evaluate the quality of an image mosaic in a quantitative way. One method focuses on the perceptual color accuracy of the mosaic reproduction, while the other concentrates on edge replication. Both measures include preprocessing to take into account the unique visual features present in an image mosaic. Doing so minimizes quality penalization due the inherent properties of an image mosaic that make them visually appealing

    The structure of gravel-bed flow with intermediate submergence: a laboratory study

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    The paper reports an experimental study of the flow structure over an immobile gravel bed in open channel at intermediate submergence, with particular focus on the near-bed region. The experiments consisted of velocity measurements using three-component (stereoscopic) Particle Image Velocimetry (PIV) in near-bed horizontal plane and two-component PIV in three vertical planes that covered three distinctly different hydraulic scenarios where the ratio of flow depth to roughness height (i.e., relative submergence) changes from 7.5 to 10.8. Detailed velocity measurements were supplemented with fine-scale bed elevation data obtained with a laser scanner. The data revealed longitudinal low-momentum and high-momentum "strips'' in the time-averaged velocity field, likely induced by secondary currents. This depth-scale pattern was superimposed with particle-scale patches of flow heterogeneity induced by gravel particle protrusions. A similar picture emerged when considering second-order velocity moments. The interaction between the flow field and gravel-bed protrusions is assessed using cross correlations of velocity components and bed elevations in a horizontal plane just above gravel particle crests. The cross correlations suggest that upward and downward fluid motions are mainly associated with upstream-facing and lee sides of particles, respectively. Results also show that the relative submergence affects the turbulence intensity profiles for vertical velocity over the whole flow depth, while only a weak effect, limited to the near-bed region, is noticed for streamwise velocity component. The approximation of mean velocity profiles with a logarithmic formula reveals that log-profile parameters depend on relative submergence, highlighting inapplicability of a conventional "universal'' logarithmic law for gravel-bed flows with intermediate submergence

    Bag-of-Features Image Indexing and Classification in Microsoft SQL Server Relational Database

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    This paper presents a novel relational database architecture aimed to visual objects classification and retrieval. The framework is based on the bag-of-features image representation model combined with the Support Vector Machine classification and is integrated in a Microsoft SQL Server database.Comment: 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF), Gdynia, Poland, 24-26 June 201
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