27,896 research outputs found

    Taking video cameras into the classroom.

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    Research into the communication and interactions in classrooms need to take the multimodal nature of classrooms into account. Video cameras can capture the dynamics of teaching and learning, but the use of videos for research purposes needs to be well thought through in order to accommodate the challenges this tool holds. This article refers to three research projects where videos were used to generate data. It is argued that videos allow the researcher to hone in on the micro-details and, in contrast to other data generation tools, allows researchers who were not present at the time to view what has been witnessed. A video recording is a data source but not data by itself and the information that is discerned from a video is framed and shaped by the research paradigm and the questions asked

    Communicating with Citizens on the Ground: A Practical Study

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    Availability and access to information is critical for a highly effective response to an ongoing event however, information reported by citizens is based on their context, bias and subjective interpretation, and the channel of communication may be too narrow to provide clear, accurate reporting. This can often lead to inadequate response to an emergency, which can in turn result in loss of property or even lives. Excessive response to an emergency can also result in a waste of highly resources. Our solution to address this problem is to make the citizen act as a camera for the control room by exploiting the user’s mobile camera. The system is designed to provide a live view of the citizen’s immediate surroundings, while control room personnel can provide instructions. In this paper, we introduce our approach and share initial insights from a focus group validation session and then four evaluations with users within a separate but closely related domain. We discuss our observations, evaluation results and provide a set of recommendations for the Emergency Response domain

    'This Video is Unavailable': Analyzing Copyright Takedown of User-Generated Content on YouTube

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    What factors lead a copyright owner to request removal of potentially infringing user-generated content? So-called “notice-and-takedown” measures are provided in the United States under Section 512 of the U.S. Copyright Act (as amended by the Digital Millennium Copyright Act 1998) and enabled in the European Union under the Directive on Electronic Commerce (2000/31/EC). While the combination of limiting liability (“safe harbor”) and notice-and-takedown procedures was originally conceived as a means of balancing innovation with the interests of rightholders, there has been limited empirical study regarding their effects. This research investigates, for the first time, the factors that motivate takedown of user-generated content by copyright owners. We study takedowns within an original dataset of 1,839 YouTube music video parodies observed between January 2012 and December 2016. We find an overall rate of takedowns within the sample of 32.9% across the 4-year period. We use a Cox proportional hazards model to investigate propositions from rightholder groups about the factors that motivate takedowns: these include concerns about commercial substitution; artistic/moral concerns; cultural differences between firms; and YouTube uploader practices. The main finding is that policy concerns frequently raised by rightholders are not associated with statistically significant patterns of action. For example, the potential for reputational harm from parodic use does not appear to predict takedown behavior. Nor does commercial popularity of the original music track trigger a systematic response from rightholders. Instead, music genre and production values emerge as significant factors. We suggest that evolving policy on intermediary liability - for example with respect to imposing filtering systems (automatically ensuring “stay-down” of potentially infringing content) - should be carefully evaluated against evidence of actual behavior, which this study shows may differ materially from stated policy positions

    Identification, synchronisation and composition of user-generated videos

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    Cotutela Universitat Politècnica de Catalunya i Queen Mary University of LondonThe increasing availability of smartphones is facilitating people to capture videos of their experience when attending events such as concerts, sports competitions and public rallies. Smartphones are equipped with inertial sensors which could be beneficial for event understanding. The captured User-Generated Videos (UGVs) are made available on media sharing websites. Searching and mining of UGVs of the same event are challenging due to inconsistent tags or incorrect timestamps. A UGV recorded from a fixed location contains monotonic content and unintentional camera motions, which may make it less interesting to playback. In this thesis, we propose the following identification, synchronisation and video composition frameworks for UGVs. We propose a framework for the automatic identification and synchronisation of unedited multi-camera UGVs within a database. The proposed framework analyses the sound to match and cluster UGVs that capture the same spatio-temporal event, and estimate their relative time-shift to temporally align them. We design a novel descriptor derived from the pairwise matching of audio chroma features of UGVs. The descriptor facilitates the definition of a classification threshold for automatic query-by-example event identification. We contribute a database of 263 multi-camera UGVs of 48 real-world events. We evaluate the proposed framework on this database and compare it with state-of-the-art methods. Experimental results show the effectiveness of the proposed approach in the presence of audio degradations (channel noise, ambient noise, reverberations). Moreover, we present an automatic audio and visual-based camera selection framework for composing uninterrupted recording from synchronised multi-camera UGVs of the same event. We design an automatic audio-based cut-point selection method that provides a common reference for audio and video segmentation. To filter low quality video segments, spatial and spatio-temporal assessments are computed. The framework combines segments of UGVs using a rank-based camera selection strategy by considering visual quality scores and view diversity. The proposed framework is validated on a dataset of 13 events (93~UGVs) through subjective tests and compared with state-of-the-art methods. Suitable cut-point selection, specific visual quality assessments and rank-based camera selection contribute to the superiority of the proposed framework over the existing methods. Finally, we contribute a method for Camera Motion Detection using Gyroscope for UGVs captured from smartphones and design a gyro-based quality score for video composition. The gyroscope measures the angular velocity of the smartphone that can be use for camera motion analysis. We evaluate the proposed camera motion detection method on a dataset of 24 multi-modal UGVs captured by us, and compare it with existing visual and inertial sensor-based methods. By designing a gyro-based score to quantify the goodness of the multi-camera UGVs, we develop a gyro-based video composition framework. A gyro-based score substitutes the spatial and spatio-temporal scores and reduces the computational complexity. We contribute a multi-modal dataset of 3 events (12~UGVs), which is used to validate the proposed gyro-based video composition framework.El incremento de la disponibilidad de teléfonos inteligentes o smartphones posibilita a la gente capturar videos de sus experiencias cuando asisten a eventos así como como conciertos, competiciones deportivas o mítines públicos. Los Videos Generados por Usuarios (UGVs) pueden estar disponibles en sitios web públicos especializados en compartir archivos. La búsqueda y la minería de datos de los UGVs del mismo evento son un reto debido a que los etiquetajes son incoherentes o las marcas de tiempo erróneas. Por otra parte, un UGV grabado desde una ubicación fija, contiene información monótona y movimientos de cámara no intencionados haciendo menos interesante su reproducción. En esta tesis, se propone una identificación, sincronización y composición de tramas de vídeo para UGVs. Se ha propuesto un sistema para la identificación y sincronización automática de UGVs no editados provenientes de diferentes cámaras dentro de una base de datos. El sistema propuesto analiza el sonido con el fin de hacerlo coincidir e integrar UGVs que capturan el mismo evento en el espacio y en el tiempo, estimando sus respectivos desfases temporales y alinearlos en el tiempo. Se ha diseñado un nuevo descriptor a partir de la coincidencia por parejas de características de la croma del audio de los UGVs. Este descriptor facilita la determinación de una clasificación por umbral para una identificación de eventos automática basada en búsqueda mediante ejemplo (en inglés, query by example). Se ha contribuido con una base de datos de 263 multi-cámaras UGVs de un total de 48 eventos reales. Se ha evaluado la trama propuesta en esta base de datos y se ha comparado con los métodos elaborados en el estado del arte. Los resultados experimentales muestran la efectividad del enfoque propuesto con la presencia alteraciones en el audio. Además, se ha presentado una selección automática de tramas en base a la reproducción de video y audio componiendo una grabación ininterrumpida de multi-cámaras UGVs sincronizadas en el mismo evento. También se ha diseñado un método de selección de puntos de corte automático basado en audio que proporciona una referencia común para la segmentación de audio y video. Con el fin de filtrar segmentos de videos de baja calidad, se han calculado algunas medidas espaciales y espacio-temporales. El sistema combina segmentos de UGVs empleando una estrategia de selección de cámaras basadas en la evaluación a través de un ranking considerando puntuaciones de calidad visuales y diversidad de visión. El sistema propuesto se ha validado con un conjunto de datos de 13 eventos (93 UGVs) a través de pruebas subjetivas y se han comparado con los métodos elaborados en el estado del arte. La selección de puntos de corte adecuados, evaluaciones de calidad visual específicas y la selección de cámara basada en ranking contribuyen en la mejoría de calidad del sistema propuesto respecto a otros métodos existentes. Finalmente, se ha realizado un método para la Detección de Movimiento de Cámara usando giróscopos para las UGVs capturadas desde smartphones y se ha diseñado un método de puntuación de calidad basada en el giro. El método de detección de movimiento de la cámara con una base de datos de 24 UGVs multi-modales y se ha comparado con los métodos actuales basados en visión y sistemas inerciales. A través del diseño de puntuación para cuantificar con el giróscopo cuán bien funcionan los sistemas de UGVs con multi-cámara, se ha desarrollado un sistema de composición de video basada en el movimiento del giroscopio. Este sistema basado en la puntuación a través del giróscopo sustituye a los sistemas de puntuaciones basados en parámetros espacio-temporales reduciendo la complejidad computacional. Además, se ha contribuido con un conjunto de datos de 3 eventos (12 UGVs), que se han empleado para validar los sistemas de composición de video basados en giróscopo.Postprint (published version

    Feasibility of a smartphone application to identify young children at risk for Autism Spectrum Disorder in a low-income community setting in South Africa

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    Introduction and aims More than 90% of children with Autism Spectrum Disorder (ASD) live in low- and middle-income countries (LMIC) where there is a great need for culturally appropriate, scalable and effective early identification and intervention tools. Smartphone technology and application (‘apps’) may potentially play an important role in this regard. The Autism&Beyond iPhone App was designed as a potential screening tool for ASD risk in children aged 12-72 months. Here we investigated the technical feasibility and cultural acceptability of a smartphone app to determine risk for ASD in children aged 12-72 months in a naturalistic, low-income South African community setting. Methodology 37 typically-developing African children and their parents/carers were recruited from community centres in Khayelitsha Township, Cape Town, South Africa. We implemented a mixed-methods design, collecting both quantitative and qualitative data from participants in 2 stages. In stage 1, we collected quantitative data. With appropriate ethics and consent, parents completed a short technology questionnaire about their familiarity with and access to smartphones, internet and apps, followed by electronic iPhone-based demographic and ASD-related questionnaires. Next, children were shown 3 short videos of 30s each and a mirror stimulus on a study smartphone. The smartphone front facing (“selfie”) camera recorded video of the child’s facial expressions and head movement. Automated computer algorithms quantified positive emotions and time attending to stimuli. We validated the automatic coding by a) comparing the computer-generated analysis to human coding of facial expressions in a random sample (N=9), and b) comparing automated analysis of the South African data (N=33) with a matched American sample (N=33). In stage 2, a subset of families were invited to participate in focus group discussions to provide qualitative data on accessibility, acceptability, and cultural appropriateness of the app in their local community. Results Most parents (64%) owned a smartphone of which all (100%) were Android based, and many used Apps (45%). Human-automated coding showed excellent correlation for positive emotion (ICC= 0.95, 95% CI 0.81-0.99) and no statistically significant differences were observed between the South African and American sample in % time attending to the video stimuli. South African children, however, smiled less at the Toys&Rhymes (SA mean (SD) = 14% (24); USA mean (SD) = 31% (34); p=0.05) and Bunny video (SA mean (SD) = 12% (17); USA mean (SD) = 30% (0.27); p=0.006). Analysis of focus group data indicated that parents/carers found the App relatively easy to use, and would recommend it to others in their community provided the App and data transfer were free. Conclusion The results from this pilot study suggested the App to be technically accurate, accessible and culturally acceptable to families from a low-resource environment in South Africa. Given the differences in positive emotional response between the groups, careful consideration should be given to identify suitable stimuli if % time smiling is to be used as a global marker for autism risk across cultures and environments

    A Human-Computer Duet System for Music Performance

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    Virtual musicians have become a remarkable phenomenon in the contemporary multimedia arts. However, most of the virtual musicians nowadays have not been endowed with abilities to create their own behaviors, or to perform music with human musicians. In this paper, we firstly create a virtual violinist, who can collaborate with a human pianist to perform chamber music automatically without any intervention. The system incorporates the techniques from various fields, including real-time music tracking, pose estimation, and body movement generation. In our system, the virtual musician's behavior is generated based on the given music audio alone, and such a system results in a low-cost, efficient and scalable way to produce human and virtual musicians' co-performance. The proposed system has been validated in public concerts. Objective quality assessment approaches and possible ways to systematically improve the system are also discussed
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