Laura Pozueco

Adaptable system based on Scalable Video Coding for high-quality video service

Content adaptation to a heterogeneous environment like the Internet is a key process for improving the perceived quality of the user. This paper presents an adaptive streaming system using Scalable Video Coding (SVC) technology. Using feedback information from clients about the transmission status, the server is able to select the most suitable combination of SVC layers for the available bandwidth. The estimation of the available bandwidth is carried out with non-intrusive methods, based on classic metrics such as packet loss, jitter and novel metrics like the linearity of reception times of RTP packets. The system is implemented in real equipment and the results show the correct operation and the accuracy of the system when adapting to different variations of the available bandwidth. We also study the scalability of the system when several clients access the service simultaneously, demonstrating that our system is as scalable as a non-adaptive system with SVC.

Subjective evaluation of critical success factors for a QoE aware adaptive system

For many years video content delivery has established itself as the killer application. Improving QoE on adaptive streaming is focusing many efforts in the quest for optimized methods and metrics to allow a QoE driven adaptation. Questions such as whether adaptive systems based on Scalable Video Coding improve subjective quality and in which situations or to what degree are still open issues. Tolerance and indifference thresholds for each type of content, conditions or viewer category, with regard to adaptive systems are critical success factors that are yet unresolved. We compare the performance of a complete adaptive system with the traditional, i.e. non-adaptive, approach in subjective terms. Results of surveying 75 participants show that the adaptation improves QoE under most of the evaluated conditions. Tolerance thresholds for triggering adaptation events have been identified. Users accustomed to Internet video are more critical than users that only watch TV. The under 35year old subset among the available population is generally more satisfied with the adaptive system than the older subset.

A non-intrusive estimation for high-quality Internet TV services

This paper presents a non-intrusive estimator for Internet TV services based on streaming technology. Analyzing the video packets received by the client application, the estimator is capable of selecting the most suitable encoding bitrate for the available bandwidth in the end-to-end path. The estimator has been integrated in a real client/server architecture and evaluated with different network traffic situations. The results of the performed evaluation have revealed the stability and adaptation speed as the best qualities of our proposal.

Evaluation of Text Entry Methods for Interactive Digital Television Applications with Devices Alternative to Conventional Remote Controls

ABSTRACT The popularity of Interactive Digital Television (IDTV) applications has grown in recent years, playing a significant role in today’s society. This new type of television allows users to access interactive applications in order to look for information, for communication or educational purposes, or just for fun. Most of these applications require text entry and many users expect a user experience similar to that of computers. Although the most common device to interact with television is the conventional remote control, other devices available on the market may be used in this context. Thus, in this article we aim to evaluate and compare different text input methods for IDTV applications using devices alternative to conventional remote controls. We have carried out an empirical study with 52 participants. We analyze entry speeds, error rates, and subjective impressions for six different entry methods, taking into account the particular characteristics of the users. As devices we have used a full-sized keyboard, a palm-sized keyboard, a gyroscopic remote point-select, and a modified touchpad. The fastest method is the standard keyboard, but in an IDTV context many users report discomfort and problems under low lighting conditions. Also, error rates are considerably higher with both keyboards when modifier keys need to be used. The results obtained with the gyroscopic remote and the touchpad are similar. Nevertheless, while users complain about fatigue problems with the former, their feedback about the latter is very positive. We have also observed that age is a major factor affecting the performance of the users. We expect our results to contribute to the design of new text entry methods for IDTV.

Adaptation engine for a streaming service based on MPEG-DASH

HTTP Video streaming has become a strong candidate for video transmission on the Internet thanks to the abundance of web infrastructure. With the recent standardization of the new MPEG Dynamic Adaptive Streaming over HTTP (DASH), the flexibility and implantation of adaptive video systems has increased due to the fact that DASH can operate on a conventional web infrastructure. In this paper we propose an estimation and adaptation system for DASH. The proposed adaptive algorithm is based on client buffer threshold and smooth throughput measures (based on the throughput of previous segments). Before DASH, the standard of Scalable Video Coding (SVC) also arose from the idea of adaptation. Both systems (adaptive system based on SVC and the proposed system for DASH) are compared in terms of Video Quality (VQ) metrics. The results show that the proposed system reacts properly to changes in the network capacity, while maintaining a minimum level of segments in the buffer. The user-perceived quality is better than in the SVC-based adaptive system although the generated traffic is higher.

An Architecture for a Learning Analytics System Applied to Efficient Driving

Transport companies are probably one of the greatest sources of pollution nowadays. Perhaps because these companies would like to improve this situation, or perhaps because they simply would like to reduce the petrol they consume, they are more than ever deploying plans in order to increase the efficiency of their fleets. One of the easiest and cheapest ways to achieve this is to teach their drivers how to be more efficient. Nevertheless, traditional learning approaches were only successful in the short term, according to the previous work. In order to achieve long-term results, new learning paradigms must be taken into account. Furthermore, if we combine these paradigms with a learning analytics system, optimal results may be reached for both the company and the drivers. In this paper, we present a learning analytics system applied to the efficient driving context. This learning analytics system is used as a fundamental piece in the deployment of the blended learning methodology for efficient professional driving designed by our research group. We describe the design and the integration of this system with a real product currently being used in many transport fleets. With a technical approach, we also describe the main problems found during the deployment of this system and the solutions designed to cope with these problems.

Adaptive learning for efficient driving in urban public transport

Concerns about global warming and energy costs have induced transport companies to take measures to reduce fuel consumption. Among the different options available, efficient driving is widely used, allowing a reduction in fuel consumption of around 10%. However, changing the drivers behavior is not exempt of problems. The success of efficient driving techniques in the long term is related to the motivation of the driver and, for that reason, an adaptive training system according to the drivers needs can prove much more successful than giving general instructions that do not solve their inefficiencies. Therefore, a properly description of the drivers behavior and the adaptation of the evaluation analysis to the context is a key factor for the learning process in efficient driving. In this paper we propose an adaptive learning system for efficient driving, which allows the evaluation of professional drivers of urban public transport in their work environment. With the proposed system, we can identify failure points relating to the context, making a focused evaluation. The first evaluation results show that the set of patterns designed to evaluate the application of efficient driving techniques can identify the incorrect actions of the drivers. Based on the results, it is possible to make personalized recommendations to improve driver performance.

Subjective video quality evaluation of different content types under different impairments

ABSTRACT Nowadays, access to multimedia content is one of the most demanded services on the Internet. However, the transmission of audio and video over these networks is not free of problems that negatively affect user experience. Factors such as low image quality, cuts during playback or losses of audio or video, among others, can occur and there is no clear idea about the level of distortion introduced in the perceived quality. For that reason, different impairments should be evaluated based on user opinions, with the aim of analyzing the impact in the perceived quality. In this work, we carried out a subjective evaluation of different types of impairments with different types of contents, including news, cartoons, sports and action movies. A total of 100 individuals, between the ages of 20 and 68, participated in the subjective study. Results show that short-term rebuffering events negatively affect the quality of experience and that desynchronization between audio and video is the least annoying impairment. Moreover, we found that the content type determines the subjective results according to the impairment present during the playback.

Optimización de rutas para mejora de la eficiencia en la conducción

Este trabajo ha sido financiado por la Comision Europea (proyecto GlobalBLED SMEInst-10-2016- 2017), el Plan Nacional de Investigacion (proyecto MINECO-13-TIN2013-41749-R) y el Plan PCTI del Principado de Asturias (proyecto GRUPIN-14-065).

Desarrollo de un laboratorio abierto de enjambres de robots autónomos de limpieza

En el corto plazo, la industria del robot autonomo y de los drones sera un factor de desarrollo importante. Tanto la fabricacion de los propios dispositivos, como del desarrollo del software que los hace funcionar seran actividades empresariales de importancia en el sector TIC. No obstante, el futuro de los robots de trabajo autonomo es colaborar unos con otros y con el entorno que los rodea (adaptacion al contexto). Para ello, deben de ser capaces de interactuar con otros equipos mediante protocolos de comunicacion y sistemas de razonamiento. Por ello, en este trabajo se presenta una experiencia encaminada a la obtencion de un sistema de trabajo colaborativo para que un grupo/enjambre de robots autonomos de limpieza puedan trabajar de forma conjunta. La experiencia se basa en un laboratorio abierto que permite a los alumnos proponer y realizar sus propios desarrollos. En el trabajo se presentan tanto los aspectos metodologicos de la experiencia, como los avances que se han conseguido realizar hasta la fecha.