1,720,965 research outputs found
A sensor fusion approach for measuring emotional customer experience in an intelligent retail environment
No full textCustomer experience depends not only on the aspects which retailers can easily control, but also on emotional factors that are unpredictable. In this paper, a Multi-Task MultiKernel learning approach is proposed to recognise positive users' emotion in a retail scenario. The overall system is composed by the Ultra-Wide Band (UWB) tracking system and a consumer smartwatch device. Data gathered from sensors are combined in a multi-kernel scenario to estimate shoppers emotion (i.e., valence and arousal) which is strictly correlated to different shoppers feelings. Results in term of accuracy and macro-F1 score prove the effectiveness and the suitability of the proposed approach
CNN Implementation for Semantic Heads Segmentation Using Top-View Depth Data in Crowded Environment
No full textThe paper “Convolutional Networks for semantic Heads Segmentation using Top-View Depth Data in Crowded Environment” [1] introduces an approach to track and detect people in cases of heavy occlusions based on CNNs for semantic segmentation using top-view RGB-D visual data. The purpose is the design of a novel U-Net architecture, U-Net 3, that has been modified compared to the previous ones at the end of each layer. In order to evaluate this new architecture a comparison has been made with other networks in the literature used for semantic segmentation. The implementation is in Python code using Keras API with Tensorflow library. The input data consist of depth frames, from Asus Xtion Pro Live OpenNI recordings (.oni). The dataset used for training and testing of the networks has been manually labeled and it is freely available as well as the source code. The aforementioned networks have their stand-alone Python script implementation for training and testing. A Python script for the on-line prediction in OpenNI recordings (.oni) is also provided. Evaluation of the networks has been made with different metrics implementations (precision, recall, F1 Score, Sørensen-Dice coefficient), included in the networks scripts
HMM-based activity recognition with a ceiling RGB-D camera
No full textAutomated recognition of Activities of Daily Living allows to identify possible health problems and apply corrective strategies in Ambient Assisted Living (AAL). Activities of Daily Living analysis can provide very useful information for elder care and long-term care services. This paper presents an automated RGB-D video analysis system that recognises human ADLs activities, related to classical daily actions. The main goal is to predict the probability of an analysed subject action. Thus, abnormal behaviour can be detected. The activity detection and recognition is performed using an affordable RGB-D camera. Human activities, despite their unstructured nature, tend to have a natural hierarchical structure; for instance, generally making a coffee involves a three-step process of turning on the coffee machine, putting sugar in cup and opening the fridge for milk. Action sequence recognition is then handled using a discriminative Hidden Markov Model (HMM). RADiaL, a dataset with RGB-D images and 3D position of each person for training as well as evaluating the HMM, has been built and made publicly available
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
People Detection and Tracking from an RGB-D Camera in Top-View Configuration: Review of Challenges and Applications
No full textThis paper presents a literature review on the use of RGB-D camera for people detection and tracking. Our aim is to use this state-of-the-art report to demonstrate the potential of top-view configuration for people detection and tracking applications in several sub-domains, to outline key limitations and to indicate areas of technology, where solutions for remaining challenges may be found. The survey examines the success of RGB-D cameras because of their affordability and for the additional rough depth information coupled with visual images that provide. These cameras in configuration top-view have already been successfully applied in the several fields to univocally identify people and to analyse behaviours and interactions. From this report, it emerges that detecting and tracking people can be a valuable source of information for many fields and purposes
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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