1,720,985 research outputs found
Event recognition in personal photo collections: An active learning approach
No full textIn this paper, we propose an active learning based approach to event recognition in personal photo collections to tackle the challenges due to the weakly labeled data, and the presence of irrelevant pictures in personal photo collections. Conventional approaches relying on supervised learning can not identify the relevant samples in training albums, often leading to wrong classification. In our work, we aim to utilize the concepts of active learning to choose the most relevant samples from a collection and train a classifier. We also investigate the importance of relevant images in the event recognition process, and show how the performance degrades if all images from an album, containing the irrelevant ones, are included in the process. The experimental evaluation is carried out on a benchmark dataset composed of a large number of personal photo albums. We demonstrate that the proposed strategy yields encouraging scores in the presence of irrelevant images in personal photo collections, advancing recent leading works
Optical image classification: A ground-truth design framework
No full textIn the remote sensing field, ground-truth design for collecting training samples represents a tricky and critical problem since it has a direct impact on most of the subsequent image processing and analysis steps. In this paper, we propose a novel framework for assisting a human user in designing ground-truth by photointerpretation for optical remote sensing image classification. The proposed approach is (almost) completely automatic and comprehensive since it aims at assisting the human user from the first to the last step of the process. It is based on unsupervised methods of segmentation and clustering, in order to investigate both the spatial and the spectral information in the process of ground-truth design. The resulting ground-truth is classifier-free and can be further improved by making it classifier-driven through an active learning process. To validate the proposed framework, an experimental study was conducted on very high spatial resolution and hyperspectral images acquired by the IKONOS and the Reflective Optics System Imaging Spectrometer sensors, respectively. The obtained results show the usefulness and effectiveness of the proposed approach
The S-Hock dataset: A new benchmark for spectator crowd analysis
No full textAlthough crowd analysis is a classical and extensively studied problem for the computer vision community, the vast majority of the works in the literature assume a single type of crowd, while the sociological literature classifies a number of different typologies, each one with their own distinctive traits. In this paper we focus on a particular kind of crowd referred in sociology as spectator crowd, which consists a number of people that are “interested in watching something specific that they came to see” Berlonghi (1995). This is the typical social formation that attends entertainment events like sport matches, concerts, movies, etc. In this work we present a novel dataset, the Spectators Hockey (S-Hock), containing almost 30 hours of videos recorded at an ice hockey rink during the Winter Universiade “Trentino2013”. On these data we provide a massive annotation, focusing on the spectators at different levels of detail: from high level features describing which team a person supports and if he/she knows his/her neighbors; to a lower level, where we consider standard pose information as well as atomic actions like applauding, jumping, etc. We also provide annotations for the game field, which allows us to analyze the relationship between the crowd behavior and the events of the match. Eventually we provide more than 100 million of annotations, that can be used for many different tasks spanning from standard applications, like people counting and head pose estimation, to higher level tasks, like excitement estimation and automatic summarization. We provide protocols and baseline results for all of these applications, encouraging further research in these field
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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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