1,721,004 research outputs found
3D Data Acquisition - Eurographics 2002 Tutorial Notes
3D scanners and image acquisition systems are rapidly becoming more affordable and allow to build highly accurate models of real 3D objects in a cost- and time-effective manner. This tutorial will present the potential of this technology, review the state of the art in model acquisition methods, and will discuss the 3D acquisition pipeline from physical acquisition until the final digital model. First, different optical scanning techniques (e.g. structured light triangulation, time-of-flight approaches) will briefly be presented. Other acquisition related issues including the design of the scanning studio will be discussed and evaluated. In the area of registration, we will consider both the problems of initially aligning individual scans, and of refining this alignment with variations of the Iterative Closest Point method. For scan integration and mesh reconstruction, we will compare various methods for computing, interpolating and approximating surfaces. We will then look at various ways in which surface properties such as color and reflectance can be extracted from acquired imagery. Finally, we will examine techniques for the efficient management and rendering of very large, attribute-rich meshes, including methods for the construction of simplified triangle-based representation and sample-based rendering approaches
Going Beyond Counting First Authors in Author Co-citation Analysis
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
“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
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
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
topicmodels: An R Package for Fitting Topic Models
Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables which are referred to as topics. The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm. The package includes interfaces to two algorithms for fitting topic models: the variational expectation-maximization algorithm provided by David M. Blei and co-authors and an algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.
7th ACM Symposium on Solid Modeling and Applications; Tutorial T2: A Framework for the Acquisition, Processing and Interactive Display of High Quality 3D Models
topicmodels: An R Package for Fitting Topic Models
Topic models allow the probabilistic modeling of term frequency occurrences in documents.
The fitted model can be used to estimate the similarity between documents as
well as between a set of specified keywords using an additional layer of latent variables
which are referred to as topics. The R package topicmodels provides basic infrastructure
for fitting topic models based on data structures from the text mining package tm. The
package includes interfaces to two algorithms for fitting topic models: the variational
expectation-maximization algorithm provided by David M. Blei and co-authors and an
algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors
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