1,720,976 research outputs found

    Evaluating Image-Based Interactive 3D Modeling Tools

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    Structure from Motion (SfM) is a computer vision technique used to reconstruct three-dimensional (3D) structures from a series of two-dimensional (2D) images or video frames. However, SfM tools struggle with transparent objects, reflective surfaces, and low-resolution frames. In such situations, image-based interactive 3D modeling software packages are employed to model 3D objects and measure dimensions. Our contributions to this work are twofold. First, we have introduced new tools to improve 3D modeling software packages; such tools are aimed at easing the workload for users. Second, we have conducted a comprehensive user study to evaluate the efficacy of popular 3d modeling software packages. The task is to measure certain dimensions for which ground truth measurements are already known. A relative error is calculated for every measurement. The evaluation of each software tool is done through survey form, event logs, and measurement relative error. The results of this user study clearly show that our approach to 3D modeling using multiple images has a lower relative error and produces higher quality 3D models than other software packages. In addition, it shows our new tools reduce the required time for completing a task

    Turning a Smartphone Selfie into a Studio Portrait

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    We introduce a novel algorithm that turns a flash selfie taken with a smartphone into a studio-like photograph with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in a controlled environment. For each pair, we have one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend lighting artifacts introduced by a close-up camera flash, such as specular highlights, shadows, and skin shine

    Image Sets Compression Via Patch Redundancy

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    In the last years, the development of compression algorithms for image collections (e.g., photo albums) has become very popular due to the enormous diffusion of digital photographs. Typically, current solutions create an image sequence from images of the photo album to make them suitable for compression using a High Performance Video Coding (HEVC) encoder. In this study, we investigated a different approach to compress a collection of similar images. Our main idea is to exploit the inter- and intra- patch redundancy to compress the entire set of images. In practice, our approach is equivalent to compress the image set with Vector Quantization (VQ) using a global codebook. Our tests show that our clusterization algorithm is effective for a large number of images

    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

    Conservative Ray Batching using Geometry Proxies

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    We present a method for improving batched ray traversal as was presented by Pharr et al. [PKGH97]. We propose to use conservative proxy geometry to more accurately determine whether a ray has a possibility of hitting any geometry that is storedon disk. This prevents unnecessary disk loads and thus reduces the disk bandwidth.Computer Graphics and Visualisatio

    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

    DeepFlash: Turning a flash selfie into a studio portrait

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    We present a method for turning a flash selfie taken with a smartphone into a photograph as if it was taken in a studio setting with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in an ad-hoc acquisition campaign. Each pair consists of one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend defects introduced by a close-up camera flash, such as specular highlights, shadows, skin shine, and flattened images
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