1,607 research outputs found

    Finding perceptually optimal operating points of a real time interactive video-conferencing system

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    This research aims to address issues faced by real time video-conferencing systems in locating a perceptually optimal operating point under various network and conversational conditions. In order to determine the perceptually optimal operating point of a video-conferencing system, we must first be able to conduct a fair assessment of the quality of the current operating point in the system and compare it with another operating point to determine if one is better than the other in terms of perceptual quality. However at this point in time, there does not exist one objective quality metric that can accurately and fully describe the perceptual quality of a real time video conversation. Hence there is a need for a controlled environment to allow tests to be conducted in and in which we can study different metrics and identify the best trade-offs between them. We begin by studying the components of a typical setup of a real time video-conferencing system and the impacts that various network and conversation conditions can have on the overall perceptual quality. We also look into different metrics available to measure those impacts. We then created a platform to perform black box testing on current video conferencing systems and observe how they handle the changes in operating conditions. The platform is then used to conduct a brief evaluation of the performance of Skype, a popular commercial video-conferencing system. However, we are not able to modify the system parameters of Skype. The main contribution of this thesis is the design of a new testbed that provides a controlled environment to allow tests to be conducted to determine the perceptual optimum operating point of a video conversation under specified network and conversation conditions. This testbed will allow us to modify certain parameters, such as frame rate and frame size, which were not previously possible. The testbed takes as input, two recorded videos of the two speakers of a face-to-face conversation and desired output video parameters, such as frame rate, frame size and delay. A video generation algorithm is designed as part of the testbed to handle modifications to frame rate and frame size of the videos as well as delays inserted into the recorded video conversation to simulate the effects of network delays. The most important issue addressed is the generation of new frames to fill up the gaps created due to a change in frame rate or delay inserted, unlike as in the case of voice, where a period of silence can simply be used to handle these situations. The testbed uses a packetization strategy designed on the basis of an uneven packet transmission rate (UPTR) and that handles the packetization of interleaved video and audio data; it also uses piggybacking to provide redundancy if required. Losses can be injected either randomly or based on packet traces collected via PlanetLab. The processed videos will then be pieced together side-by-side to give the viewpoint of a third-party observing the video conversation from the site of the first speaker. Hence the first speaker will be observed to have a faster reaction time without network delays than that of the second speaker who is simulated to be located at the remote end. The video of the second speaker will also reflect the degradations in perceptual quality induced by the network conditions, whereas the first speaker will be of perfect quality. Hence with the testbed, we are able to generate output videos for different operating points under the same network and conversational conditions and thus able to make comparisons between two operating points. With the testbed in place, we demonstrate how it can be used to evaluate the effects of various parameters on the overall perceptual quality. Lastly, we demonstrate the results of applying an existing efficient search algorithm used for estimating the perceptually optimal mouth-to-ear delay (MED) of a Voice-over-IP(VoIP) conversation to a Video Conversation. This is achieved by using the network simulator designed to conduct a series of subjective and objective tests to identify the perceptual optimum MED under specific network and conversational conditions

    Using natural user interfaces to support synchronous distributed collaborative work

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    Synchronous Distributed Collaborative Work (SDCW) occurs when group members work together at the same time from different places together to achieve a common goal. Effective SDCW requires good communication, continuous coordination and shared information among group members. SDCW is possible because of groupware, a class of computer software systems that supports group work. Shared-workspace groupware systems are systems that provide a common workspace that aims to replicate aspects of a physical workspace that is shared among group members in a co-located environment. Shared-workspace groupware systems have failed to provide the same degree of coordination and awareness among distributed group members that exists in co-located groups owing to unintuitive interaction techniques that these systems have incorporated. Natural User Interfaces (NUIs) focus on reusing natural human abilities such as touch, speech, gestures and proximity awareness to allow intuitive human-computer interaction. These interaction techniques could provide solutions to the existing issues of groupware systems by breaking down the barrier between people and technology created by the interaction techniques currently utilised. The aim of this research was to investigate how NUI interaction techniques could be used to effectively support SDCW. An architecture for such a shared-workspace groupware system was proposed and a prototype, called GroupAware, was designed and developed based on this architecture. GroupAware allows multiple users from distributed locations to simultaneously view and annotate text documents, and create graphic designs in a shared workspace. Documents are represented as visual objects that can be manipulated through touch gestures. Group coordination and awareness is maintained through document updates via immediate workspace synchronization, user action tracking via user labels and user availability identification via basic proxemic interaction. Members can effectively communicate via audio and video conferencing. A user study was conducted to evaluate GroupAware and determine whether NUI interaction techniques effectively supported SDCW. Ten groups of three members each participated in the study. High levels of performance, user satisfaction and collaboration demonstrated that GroupAware was an effective groupware system that was easy to learn and use, and effectively supported group work in terms of communication, coordination and information sharing. Participants gave highly positive comments about the system that further supported the results. The successful implementation of GroupAware and the positive results obtained from the user evaluation provides evidence that NUI interaction techniques can effectively support SDCW

    Multi-party holomeetings: toward a new era of low-cost volumetric holographic meetings in virtual reality

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    © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Fueled by advances in multi-party communications, increasingly mature immersive technologies being adopted, and the COVID-19 pandemic, a new wave of social virtual reality (VR) platforms have emerged to support socialization, interaction, and collaboration among multiple remote users who are integrated into shared virtual environments. Social VR aims to increase levels of (co-)presence and interaction quality by overcoming the limitations of 2D windowed representations in traditional multi-party video conferencing tools, although most existing solutions rely on 3D avatars to represent users. This article presents a social VR platform that supports real-time volumetric holographic representations of users that are based on point clouds captured by off-the-shelf RGB-D sensors, and it analyzes the platform’s potential for conducting interactive holomeetings (i.e., holoconferencing scenarios). This work evaluates such a platform’s performance and readiness for conducting meetings with up to four users, and it provides insights into aspects of the user experience when using single-camera and low-cost capture systems in scenarios with both frontal and side viewpoints. Overall, the obtained results confirm the platform’s maturity and the potential of holographic communications for conducting interactive multi-party meetings, even when using low-cost systems and single-camera capture systems in scenarios where users are sitting or have a limited translational movement along the X, Y, and Z axes within the 3D virtual environment (commonly known as 3 Degrees of Freedom plus, 3DoF+).The authors would like to thank the members of the EU H2020 VR-Together consortium for their valuable contributions, especially Marc Martos and Mohamad Hjeij for their support in developing and evaluating tasks. This work has been partially funded by: the EU’s Horizon 2020 program, under agreement nº 762111 (VR-Together project); by ACCIÓ (Generalitat de Catalunya), under agreement COMRDI18-1-0008 (ViVIM project); and by Cisco Research and the Silicon Valley Community Foundation, under the grant Extended Reality Multipoint Control Unit (ID: 1779376). The work by Mario Montagud has been additionally funded by Spain’s Agencia Estatal de Investigación under grant RYC2020-030679-I (AEI / 10.13039/501100011033) and by Fondo Social Europeo. The work of David Rincón was supported by Spain’s Agencia Estatal de Investigación within the Ministerio de Ciencia e Innovación under Project PID2019-108713RB-C51 MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version

    Abordando la medición automática de la experiencia de la audiencia en línea

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    Trabajo de Fin de Grado del Doble Grado en Ingeniería Informática y Matemáticas, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2020/2021The availability of automatic and personalized feedback is a large advantage when facing an audience. An effective way to give such feedback is to analyze the audience experience, which provides valuable information about the quality of a speech or performance. In this document, we present the design and implementation of a computer vision system to automatically measure audience experience. This includes the definition of a theoretical and practical framework grounded on the theatrical perspective to quantify this concept, the development of an artificial intelligence system which serves as a proof-of-concept of our approach, and the creation of a dataset to train our system. To facilitate the data collection step, we have also created a custom video conferencing tool. Additionally, we present the evaluation of our artificial intelligence system and the final conclusions.La disponibilidad de feedback automático y personalizado supone una gran ventaja a la hora de enfrentarse a un público. Una forma efectiva de dar este tipo de feedback es analizar la experiencia de la audiencia, que proporciona información fundamental sobre la calidad de una ponencia o actuación. En este documento exponemos el diseño e implementación de un sistema automático de medición de la experiencia de la audiencia basado en la visión por computador. Esto incluye la definición de un marco teórico y práctico fundamentado en la perspectiva del mundo del teatro para cuantificar el concepto de experiencia de la audiencia, el desarrollo de un sistema basado en inteligencia artificial que sirve como prototipo de nuestra aproximación y la recopilación un conjunto de datos para entrenar el sistema. Para facilitar este último paso hemos desarrolado una aplicación de videoconferencias personalizada. Además, en este trabajo presentamos la evaluación de nuestro sistema de inteligencia artificial y las conclusiones extraídas.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

    Video Quality Metrics

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