Author
Andrea Ferracani
Bio: Andrea Ferracani is an academic researcher from University of Florence. The author has contributed to research in topics: Ontology (information science) & Web application. The author has an hindex of 9, co-authored 54 publications receiving 302 citations.
Papers
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TL;DR: The MNEMOSYNE system is described, which builds a profile of the artworks of interest for each visitor, which is used to drive an interactive table that personalizes multimedia content delivery and a recommendation system to personalize exploration of multimedia content.
Abstract: The amount of multimedia data collected in museum databases is growing fast, while the capacity of museums to display information to visitors is acutely limited by physical space. Museums must seek the perfect balance of information given on individual pieces in order to provide sufficient information to aid visitor understanding while maintaining sparse usage of the walls and guaranteeing high appreciation of the exhibit. Moreover, museums often target the interests of average visitors instead of the entire spectrum of different interests each individual visitor might have. Finally, visiting a museum should not be an experience contained in the physical space of the museum but a door opened onto a broader context of related artworks, authors, artistic trends, etc. In this paper we describe the MNEMOSYNE system that attempts to address these issues through a new multimedia museum experience. Based on passive observation, the system builds a profile of the artworks of interest for each visitor. These profiles of interest are then used to drive an interactive table that personalizes multimedia content delivery. The natural user interface on the interactive table uses the visitor's profile, an ontology of museum content and a recommendation system to personalize exploration of multimedia content. At the end of their visit, the visitor can take home a personalized summary of their visit on a custom mobile application. In this article we describe in detail each component of our approach as well as the first field trials of our prototype system built and deployed at our permanent exhibition space at LeMurate (http://www.lemurate.comune.fi.it/lemurate/) in Florence together with the first results of the evaluation process during the official installation in the National Museum of Bargello (http://www.uffizi.firenze.it/musei/?m=bargello).
49 citations
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16 Oct 2016TL;DR: This paper evaluates methods to move 'naturally' in an Immersive Virtual Environment (IVE) visualised through an Head Mounted Display (HMD) and shows that one of the methods proposed has a performance comparable to established techniques in literature.
Abstract: In this paper we evaluate methods to move 'naturally' in an Immersive Virtual Environment (IVE) visualised through an Head Mounted Display (HMD). Natural interaction is provided through gesture recognition on depth sensors' data. Gestural input solutions in the literature to provide locomotion are discussed. Two new methods for locomotion are proposed, implemented in a framework used for comparative evaluation. Perceived naturalness and effectiveness of locomotion methods are assessed through qualitative and quantitative measures. Extensive tests are conducted on the locomotion considering also: 1) obstacles in navigation; 2) interaction with virtual objects during locomotion. This is done with the aim to identify methods capable to provide a full body experience in an IVE. Results show that one of the methods for locomotion we propose has a performance comparable to established techniques in literature. Outcomes may be exploited to improve the naturalness of users' movements in IVEs and help to unlock new strategies in providing IVEs for learning, training, collaboration and entertainment, also with respect to users with disabilities.
42 citations
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TL;DR: This article addresses the problem of creating a smart audio guide that adapts to the actions and interests of museum visitors by proposing the use of a compact Convolutional Neural Network that performs object classification and localization.
Abstract: In this article, we address the problem of creating a smart audio guide that adapts to the actions and interests of museum visitors. As an autonomous agent, our guide perceives the context and is able to interact with users in an appropriate fashion. To do so, it understands what the visitor is looking at, if the visitor is moving inside the museum hall, or if he or she is talking with a friend. The guide performs automatic recognition of artworks, and it provides configurable interface features to improve the user experience and the fruition of multimedia materials through semi-automatic interaction.Our smart audio guide is backed by a computer vision system capable of working in real time on a mobile device, coupled with audio and motion sensors. We propose the use of a compact Convolutional Neural Network (CNN) that performs object classification and localization. Using the same CNN features computed for these tasks, we perform also robust artwork recognition. To improve the recognition accuracy, we perform additional video processing using shape-based filtering, artwork tracking, and temporal filtering. The system has been deployed on an NVIDIA Jetson TK1 and a NVIDIA Shield Tablet K1 and tested in a real-world environment (Bargello Museum of Florence).
40 citations
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07 Nov 2014TL;DR: A natural interface featuring an interactive virtual environment that aims to train medical professionals in following security procedures proposed by the WHO adopting a `serious game' approach is introduced.
Abstract: Serious games have been widely exploited in medicine training and rehabilitations. Although many medical simulators exist with the aim to train personal skills of medical operators, only few of them take into account cooperation between team members. After the introduction of the Surgical Safety Checklist by the World Health Organization (WHO), that has to be carried out by surgical team members, several studies have proved that the adoption of this procedure can remarkably reduce the risk of surgical crisis. In this paper we introduce a natural interface featuring an interactive virtual environment that aims to train medical professionals in following security procedures proposed by the WHO adopting a `serious game' approach. The system presents a realistic and immersive 3D interface and allows multiple users to interact using vocal input and hand gestures. Natural interactions between users and the simulator are obtained exploiting the Microsoft Kinect\texttrademark~sensor. The game can be seen as a role play game in which every trainee has to perform the correct steps of the checklist accordingly to his/her professional role in the medical team.
26 citations
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19 Oct 2017TL;DR: A system for immersive experiences in museums using Voice Commands (VCs) and Virtual Reality (VR) and specifically designed for use by people with motor disabilities is presented.
Abstract: In this demo we present a system for immersive experiences in museums using Voice Commands (VCs) and Virtual Reality (VR). The system has been specifically designed for use by people with motor disabilities. Natural interaction is provided through Automatic Speech Recognition (ASR) and allows to experience VR environments wearing an Head Mounted Display (HMD), i.e. the Oculus Rift. Insights gathered during the implementation and results from an initial usability evaluation are reported.
22 citations
Cited by
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TL;DR: This paper bridges the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas, and provides an encyclopedic review of mobile and Wireless networking research based on deep learning, which is categorize by different domains.
Abstract: The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. Fulfilling these tasks is challenging, as mobile environments are increasingly complex, heterogeneous, and evolving. One potential solution is to resort to advanced machine learning techniques, in order to help manage the rise in data volumes and algorithm-driven applications. The recent success of deep learning underpins new and powerful tools that tackle problems in this space. In this paper, we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas. We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking. We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems. Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains. Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.
975 citations
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TL;DR: The abstract should not contain any undefined abbreviations or unspecified references, and work planned but not completed should not appear in the abstract.
Abstract: Please provide a short abstract of 100 to 250 words. The abstract should not contain any undefined abbreviations or unspecified references. Work planned but not completed should not appear in the abstract.
520 citations
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TL;DR: A comprehensive overview of the current progress in NST can be found in this paper, where the authors present several evaluation methods and compare different NST algorithms both qualitatively and quantitatively, concluding with a discussion of various applications of NST and open problems for future research.
Abstract: The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks (CNNs) in creating artistic imagery by separating and recombining image content and style. This process of using CNNs to render a content image in different styles is referred to as Neural Style Transfer (NST). Since then, NST has become a trending topic both in academic literature and industrial applications. It is receiving increasing attention and a variety of approaches are proposed to either improve or extend the original NST algorithm. In this paper, we aim to provide a comprehensive overview of the current progress towards NST. We first propose a taxonomy of current algorithms in the field of NST. Then, we present several evaluation methods and compare different NST algorithms both qualitatively and quantitatively. The review concludes with a discussion of various applications of NST and open problems for future research. A list of papers discussed in this review, corresponding codes, pre-trained models and more comparison results are publicly available at this https URL.
383 citations
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TL;DR: In this article, the authors provide an encyclopedic review of mobile and wireless networking research based on deep learning, which they categorize by different domains and discuss how to tailor deep learning to mobile environments.
Abstract: The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, agile management of network resource to maximize user experience, and extraction of fine-grained real-time analytics. Fulfilling these tasks is challenging, as mobile environments are increasingly complex, heterogeneous, and evolving. One potential solution is to resort to advanced machine learning techniques to help managing the rise in data volumes and algorithm-driven applications. The recent success of deep learning underpins new and powerful tools that tackle problems in this space.
In this paper we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas. We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking. We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems. Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains. Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.
300 citations
27 Dec 2017
TL;DR: A systematic review of the use of virtual reality in education, as well as two distinct thematic analyses that indicate that the majority of researchers use virtual reality to increase the intrinsic motivation of students, and refer to a narrow range of factors such as constructivist pedagogy, collaboration, and gamification in the design of their experiences.
Abstract: Virtual reality has existed in the realm of education for over half a century. However, its widespread adoption is still yet to occur. This is a result of a myriad of limitations to both the technologies themselves, and the costs and logistics required to deploy them. In order to gain a better understanding of what these issues are, and what it is that educators hope to gain by using these technologies in the first place, we have performed both a systematic review of the use of virtual reality in education, as well as two distinct thematic analyses. The first analysis investigated the applications and reported motivations provided by educators in academic literature for developing virtual reality educational systems, while the second investigated the reported problems associated with doing so. These analyses indicate that the majority of researchers use virtual reality to increase the intrinsic motivation of students, and refer to a narrow range of factors such as constructivist pedagogy, collaboration, and gamification in the design of their experiences. Similarly, a small number of educational areas account for the vast majority of educational virtual reality implementations identified in our analyses. Next, we introduced and compared a multitude of recent virtual reality technologies, discussing their potential to overcome several of the problems identified in our analyses, including cost, user experience and interactivity. However, these technologies are not without their own issues, thus we conclude this paper by providing several novel techniques to potentially address them, as well as potential directions for future researchers wishing to apply these emerging technologies to education.
248 citations