Multi-user video streaming using unequal error protection network coding in wireless networks

In this paper, we investigate a multi-user video streaming system applying unequal error protection (UEP) network coding (NC) for simultaneous real-time exchange of scalable video streams among multiple users. We focus on a simple wireless scenario where users exchange encoded data packets over a common central network node (e.g., a base station or an access point) that aims to capture the fundamental system behaviour. Our goal is to present analytical tools that provide both the decoding probability analysis and the expected delay guarantees for different importance layers of scalable video streams. Using the proposed tools, we offer a simple framework for design and analysis of UEP NC based multi-user video streaming systems and provide examples of system design for video conferencing scenario in broadband wireless cellular networks

No-reference depth map quality evaluation model based on depth map edge confidence measurement in immersive video applications

When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance

Caracterización semántica de espacios: Sistema de Videovigilancia Inteligente en Smart Cities

Esta Tesis Doctoral, realizada dentro del proyecto europeo HuSIMS - Human Situation Monitoring System, presenta una metodología inteligente para la caracterización de escenarios capaz de detectar e identificar situaciones anómalas analizando el movimiento de los objetos. El sistema está diseñado para reducir al mínimo el procesamiento y la transmisión de vídeo permitiendo el despliegue de un gran número de cámaras y sensores, y por lo tanto adecuada para Smart Cities. Se propone un enfoque en tres etapas. Primero, la detección de objetos en movimiento en las propias cámaras, utilizando algorítmica sencilla, evitando el envío de datos de vídeo. Segundo, la construcción de un modelo de las zonas de las escenas utilizando los parámetros de movimiento identificados previamente. Y tercero, la realización de razonado semántico sobre el modelo de rutas y los parámetros de los objetos de la escena actual para identificar las alarmas reconociendo la naturaleza de los eventosDepartamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemátic