238 research outputs found

    Networked digital media

    Full text link

    MediaSync: Handbook on Multimedia Synchronization

    Get PDF
    This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

    Inertial Sensing for Human Motion Analysis: Processing, Technologies, and Applications

    Get PDF
    Human motion has always attracted significant interest and curiosity. In particular, the last two centuries have seen a fast and great development of innovative techniques and technologies for the scientific analysis of human motion. If initially this was mainly due to the large interest in biomedical fields, a growing number of other leading applications has kept this interest alive until today. These applications emerge, for instance, in sport, entertainment, and industrial contexts. The first motion capture systems, appeared along the nineteenth century, were typically based on optical technologies and their development was profoundly interlaced with the contemporary development of photography and cinematography. Since then, many other different technologies have been employed to develop new motion capture systems, such as (but not limited to) inertial, mechanical, magnetic, and acoustic. In particular, inertial motion capture systems, based on the use of inertial sensors (such as the accelerometer, which measures the acceleration, and the gyroscope, which measures angular velocity), are likely to replace the previous ones and become a standard technology. This is mainly favored by the recent great improvement in the large-scale development of accurate inertial sensors ever cheaper. When referring to inertial human motion analysis, several application areas are driving current research and development efforts. A tentative list may include, for instance, the following: clinical and home monitoring and/or rehabilitation; ambient assisted living; computer graphics and computer animation; gaming and virtual reality; sport training; pedestrian navigation; and robotics. Furthermore, human motion analysis often implies a transversal investigation of many aspects of human motion, at different levels of abstraction and at different detail depths. For instance, one may just be interested in recognizing and estimating the pose of a person as well as in identifying the activities and/or the gestures that he/she is performing. Furthermore, one may be just interested in analyzing a restricted part of the body rather than focusing on the full body. Due to this heterogeneity of topics and intents, this thesis does not focus on a specific application or method, but aims at investigating different aspects of inertial human motion analysis, by specifically discussing the corresponding data processing approaches and the involved technologies. Four research areas have been taken into account which correspond to four types of applications: arm posture recognition; activity classification; evaluation of functional motor tasks; and motion reconstruction. In particular, these applications have been chosen in order to cover topics with different levels of abstraction and different detail depths

    Sensing and Signal Processing in Smart Healthcare

    Get PDF
    In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included

    2009-2010 Course Catalog

    Get PDF
    2009-2010 Course Catalo

    2000-2002 Course Catalog

    Get PDF
    2000-2002 Course Catalo

    Vernacular Posthumanism: Visual Culture and Material Imagination

    Get PDF
    Vernacular Posthumanism: Visual Culture and Material Imagination uses a theory of image vernaculars in order to explore the ways in which contemporary visual culture both reflects on and constructs 21st century cultural attitudes toward the human and the nonhuman. This project argues that visual culture manifests a vernacular posthumanism that expresses a fundamental contradiction: the desire to transcend the human while at the same time reasserting the importance of the flesh and the materiality of lived experience. This contradiction is based in a biodeterminist desire, one that fantasizes about reducing all actants, both human and nonhuman, to functions of code. Within this framework, actants become fundamentally exchangeable, able to be combined, manipulated, and understood as variations of digital code. Visual culture – and its expression of vernacular posthumanism – thus functions as a reflection on contemporary conceptualizations of the human, a rehearsal of the posthuman, and a staging ground for encounters between the human and the nonhuman. Each chapter of this project begins in the field of film studies and then moves out toward a broader analysis of visual culture and nonhumanist theory. This project relies on the theories and methodologies of phenomenology, materialism, posthumanism, object-oriented ontology, actor-network theory, film and media studies, and visual culture studies. Visual objects analyzed include: the films of Stanley Kubrick, David Cronenberg, and Krzysztof Kieślowski; Fast, Cheap & Out of Control (1997); the film 300 (2006); the TV series Planet Earth (2006); DNA portraits, the art of Damien Hirst; Body Worlds; human migration maps; and remote surgical machinery

    2018-2019 Course Catalog

    Get PDF
    2018-2019 Course Catalo

    Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks

    Get PDF
    Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming concern in regard to the physical infrastructure security, safety and privacy has arisen due to the potential of their use in malicious activities. To address this problem, we propose a novel solution that automates the drone detection and identification processes using a drone’s acoustic features with different deep learning algorithms. However, the lack of acoustic drone datasets hinders the ability to implement an effective solution. In this paper, we aim to fill this gap by introducing a hybrid drone acoustic dataset composed of recorded drone audio clips and artificially generated drone audio samples using a state-of-the-art deep learning technique known as the Generative Adversarial Network. Furthermore, we examine the effectiveness of using drone audio with different deep learning algorithms, namely, the Convolutional Neural Network, the Recurrent Neural Network and the Convolutional Recurrent Neural Network in drone detection and identification. Moreover, we investigate the impact of our proposed hybrid dataset in drone detection. Our findings prove the advantage of using deep learning techniques for drone detection and identification while confirming our hypothesis on the benefits of using the Generative Adversarial Networks to generate real-like drone audio clips with an aim of enhancing the detection of new and unfamiliar drones

    2017-2018 Course Catalog

    Get PDF
    2017-2018 Course Catalo
    • …
    corecore