1,720,956 research outputs found

    A cooperative Top-Down/Bottom-Up Technique for Motion Field Segmentation

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    The segmentation of video sequences into regions underlying a coherent motion is one of the most useful processing for video analysis and coding. In this paper, we propose an algorithm that exploits the advantages of both top-down and bottom-up techniques for motion eld segmentation. To remove camera motion, a global motion estimation and compensation is rst performed. Local motion estimation is then carried out relying on a traslational motion model. Starting from this motion eld, a two-stage analysis based on ane models takes place. In the rst stage, using a top-down segmentation technique, macro-regions with coherent ane motion are extracted. In the second stage, the segmentation of each macro-region is rened using a bottom-up approach based on a motion vector clustering. In order to further improve the accuracy of the spatio-temporal segmentation, a Markov Random Field (MRF)-inspired motion-and-intensity based renement step is performed to adjust objects boundaries

    A Robust Region Merging Technique for Video Sequence Spatio-Temporal Segmentation

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    The segmentation of video sequences into regions underlying a coherent motion is one of the most important processing in video analysis and coding. In this paper, we propose a reliability measure that indicates to what extent an affine motion model represents the motion of an image region. This reliability measure is then proposed as a criterion to coherently merge moving image regions in a Minimum Description Length (MDL) framework. To overcome the region-based motion estimation and segmentation chicken and egg problem, the motion field estimation and the segmentation task are treated separately. After a global motion compensation, a local motion field estimation is carried out starting from a translational motion model. Concurrently, a Markov Random Field model based algorithm provides for an initial static image partition. The motion estimation and segmentation problem is then formulated in the view of the MDL principle. A merging stage based on a directed weighted graph gives the final spatio-temporal segmentation. The simulation results show the effectiveness of the proposed algorithm

    MDL-Based Coherent Motion Segmentation for Semantic Object Identification

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    The extraction of semantically meaningful objects that can describe a video sequence provides great expectations for video compression and retrieval. In this paper we propose an effective region merging technique that coherently merge moving image regions in a Minimum Description Length framework. This technique uses a reliability measure that indicates to what extent an affine parameter set represent the motion of an image region. To overcome the region-based motion estimation and segmentation chicken and egg problem, the motion field estimation and the segmentation task are treated separately. A preliminary motion field estimation is carried out starting from a traslational motion model. Concurrently, a Markov Random Field model based algorithm provides for an initial static image partition. For each image region of this spatial segmentation, affine motion parameters are then extracted from the motion field by means of a robust linear regression algorithm. A merging stage based on the proposed technique gives the final spatio-temporal segmentation

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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