1,720,958 research outputs found
Foreground Detection Optimization for SoCs embedded on Smart Cameras
No full textIn this paper we study the effectiveness of a set of optimizations applied on a foreground detection and background maintainance algorithm. The optimizations were specifically devised to run in real time on hardware architectures embedded on commercial smart cameras. In order to achieve these aims we focused our attention on two kinds of optimizations based on the elimination of floatingpoint operations and the adoption of SIMD instructions. The optimized version of the algorithm has been tested on two RISC architectures (CRISv32 and MIPS 32Kc) considering different stream resolutions. The results confirm the effectiveness of the proposed solutions, which allows to process in real-time up to VGA resolution
Counting people by RGB or depth overhead cameras
Get PDFIn this paper we present a vision based method for counting the number of persons which cross a virtual line. The method analyzes the video stream acquired by a camera mounted in a zenithal position with respect to the counting line, allowing to determine the number of persons that cross the virtual line and providing the crossing direction for each person. The proposed approach has been specifically designed to achieve high accuracy and computational efficiency, so as to allow its adoption in real scenarios. An extensive evaluation of the method has been carried out taking into account the main factors that may impact on the counting performance and, in particular, the acquisition technology (traditional RGB camera and depth sensor), the installation scenario (indoor and outdoor), the density of the people flow (isolated people and groups of persons), the acquisition frame rate, and the image resolution. We have also analyzed the combination of the outputs obtained from the RGB and depth sensors as a way to improve the counting performance. The experimental results confirm the effectiveness of the proposed method, especially when combining RGB and depth information, and the tests over three different CPU architectures demonstrate the possibility of deploying the method both on high-end servers for processing in parallel a large number of video streams and on low power CPUs as those embedded on commercial smart cameras
Benchmarking two algorithms for people detection from top-view depth cameras
No full textAutomatic people detection from videos is an important task in many computer vision applications either for security and safety motivations or for business intelligence purposes. In order to achieve high person detection accuracy many authors propose the adoption of a depth sensor mounted in a top-view position in order to mitigate the effects of occlusions and illumination conditions on the performance. Unfortunately, most approaches presented so far in the scientific literature have been tested on very small datasets which do not account for the typical situations arising in real scenarios and consequently do not allow interested readers to figure out which method has to be used in the specific scenario at hand. In this paper we benchmark two different approaches available in the literature for people detection from a zenithal mounted depth camera; the former is an unsupervised method aimed at finding the head of persons defined as the local minimum regions in the depth map, while the latter is based on the combination of the histograms of oriented gradient description and the support vector machine classifier. The benchmarking is performed on a public dataset of images captured in two different lighting conditions and with varying number of persons; this allows to assess the performance of the considered approaches under different real world scenarios. A detailed analysis of the two methods is reported in the experimental section of the paper allowing the reader to comprehend the pros and cons of each approach on the considered scenes
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
A versatile and effective method for counting people on either RGB or depth overhead cameras
No full textIn this paper we present an innovative method for counting people from zenithal mounted cameras. The proposed method is designed to be computationally efficient and able to provide accurate counting under different realistic conditions. The method can operate with traditional surveillance cameras or with depth imaging sensors. The validation has been carried out on a significant dataset of images that has been specifically devised and collected in order to account for the main factors that may impact on the counting accuracy and, in particular, the acquisition technology (traditional RGB camera and depth sensor), the installation scenario (indoor and outdoor), the density of the people flow (isolated people and groups of persons). Results confirm that the method can achieve an accuracy ranging between 90% and 98% depending on the adopted sensor technology and on the complexity of the scenario
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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
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