The audio-visual sector is undergoing a major transformation due to the emergence of heterogeneous connected devices, including Smart TVs. This reinvention is changing the consumption habits of users, enabling new experiences in which traditional broadcasting and Internet media services are blended. Hybrid broadcast-Internet services build upon on the foundation of standards, such as hybrid broadcast broadband TV. In this context, this paper provides details on a large pilot deployment for a multi-device hybrid broadcast-Internet service for a live TV programme. It defines and describes the development and deployment of an innovative live service that Euskal Irrati Telebista, the Basque public broadcaster, provided to cover the election night in the Basque Country, Spain. This paper provides results by showing usage statistics of end-users, and presents a discussion with lessons learned about the current hybrid broadcast-Internet ecosystem and multi-device live services.

3D image rendering for virtual reality HMDs is typically generated based on a set of parameters taken from the manufacturer-supplied specifications and an idealised perspective model. But actual displays may vary in build features that alter spatial perception. Moreover, the eye focusing effort is often ignored. The resulting visual discomfort and incorrect geometry perception has discouraged use of immersive virtual reality in industrial applications. This work addresses these issues and describes a system with per-device calibration and control of stereo perspective projections and focus. The ideas presented may improve the usefulness of VR in industrial training and visualization.

Purpose The purpose of this paper is to develop a model to help RTC managers in the technological and R&D decisions and bets so as to change the perceived value of the R&D projects of the centres. To achieve this aim, the paper investigates the different models for the valuation of intangible assets. Design/methodology/approach The paper presents a single case study and focusses on creating a useful IC valuation model for the centre, using existing methods and frameworks in IP and IC fields. Findings The paper presents a new method for the calculation of IC applied to a RTC in ICT sector, in which the valuation of the IP is included (software libraries) and the KM and the peculiarities of these kinds of organisations are explained. The model is based on Edvinsson and Malone (1997) and Leitner (2005). Research limitations/implications Although the use of a single case provides rich data, it is also limits the generalisability to other RTCs. Another limitation is that not all existing methods were explained. This new method constitutes a first proposal for the IP and IC valuation in RTCs and further discussion and development would be carried out in the future. Practical implications The results suggest an IP and IC measurement model to improve the strategic and technological decisions making. Social implications This paper may favour the competitiveness of companies engaged in intangible assets (knowledge, R&D) and the negotiation of the contracts since it arrives to determine a value for the intellectual property (software libraries) and intellectual capital. Originality/value This paper proposes an IC Model orientated towards an RTC context and to provide a value perspective for them. The authors are practitioners and the model is in use.

The explosion in the variety and volume of video services makes bandwidth and latency performance of networks more critical to the user experience. The media industry's response, HTTP-based Adaptive Streaming technology, offers media players the possibility to dynamically select the most appropriate bitrate according to the connectivity performance. Moving forward, the telecom industry's move is 5G. 5G aims efficiency by dynamic network optimization to make maximum use of the resources to get as high capacity and Quality of Service (QoS) as possible. These networks will be based on software defined networking (SDN) and network function virtualization (NFV) techniques, enabling self-management functions. Here, machine learning is a key technology to reach this 5G vision. On top of machine learning, SDN and NFV, this paper provides a network resource allocator system as the main contribution which enables autonomous network management aware of quality of experience (QoE). This system predicts demand to foresee the amount of network resources to be allocated and the topology setup required to cope with the traffic demand. Furthermore, the system dynamically provisions the network topology in a proactive way, while keeping the network operation within QoS ranges. To this end, the system processes signals from multiple network nodes and end-to-end QoS and QoE metrics. This paper evaluates the system for live and on-demand dynamic adaptive streaming over HTTP and high efficiency video coding services. From the experiment results, it is concluded that the system is able to scale the network topology and to address the level of resource efficiency, required by media streaming services.

The burgeoning capabilities of Web browsers to exploit full-featured devices can turn the huge pool of social connected users into a powerful network of processing assets. HTML5 and JavaScript stacks support the deployment of social client-side processing infrastructure, while WebGL and WebCL fill the gap to gain full GPU and multi-CPU performance. Mobile Grid and Mobile Cloud Computing solutions leverage smart devices to relieve the processing tasks to be performed by the service infrastructure. Motivated to gain cost-efficiency, a social network service provider can outsource the video analysis to elements of a mobile grid as an infrastructure to complement an elastic cloud service. As long as users access to videos, batch image analysis tasks are dispatched from the server, executed in the background of the client-side hardware, and finally, results are consolidated by the server. This paper presents SaW (Social at Work) to provide a pure Web-based solution as a mobile grid to complement a cloud media service for image analysis on videos.

Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury). The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement. The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton. This approximation is rough since their kinematic structures differ. Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup. Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains. EIKPE has been tested with single DOF movements of the wrist and elbow joints. This paper presents the assessment of EIKPE with elbow-shoulder compound movements (i.e., object prehension). Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage). The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compound movement execution, especially for the shoulder joint angles. This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types.

In Robot-Assisted Rehabilitation (RAR) the accurate estimation of the patient limb joint angles is critical for assessing therapy efficacy. In RAR, the use of classic motion capture systems (MOCAPs) (e.g., optical and electromagnetic) to estimate the Glenohumeral (GH) joint angles is hindered by the exoskeleton body, which causes occlusions and magnetic disturbances. Moreover, the exoskeleton posture does not accurately reflect limb posture, as their kinematic models differ. To address the said limitations in posture estimation, we propose installing the cameras of an optical marker-based MOCAP in the rehabilitation exoskeleton. Then, the GH joint angles are estimated by combining the estimated marker poses and exoskeleton Forward Kinematics. Such hybrid system prevents problems related to marker occlusions, reduced camera detection volume, and imprecise joint angle estimation due to the kinematic mismatch of the patient and exoskeleton models. This paper presents the formulation, simulation, and accuracy quantification of the proposed method with simulated human movements. In addition, a sensitivity analysis of the method accuracy to marker position estimation errors, due to system calibration errors and marker drifts, has been carried out. The results show that, even with significant errors in the marker position estimation, method accuracy is adequate for RAR.

HTML5 is driving a strong trend towards interoperable Web-based applications, enabling a wider range of devices to run this kind of applications. The key challenge of next-generation media applications is to federate cooperative devices to provide multi-device experiences overcoming current second screen solutions within the connected TV industry. There is a gap on the experience of users, since they perceive devices as isolated pieces of applications when they would prefer to have a single experience through multiple devices at the same time. This paper proposes a unified methodology and a common specification over Web Components for the adaptation of a single application, seamlessly running different instances on one or more devices simultaneously, according to the multi-device context of the user and the specific features of the devices. The solution presented in this paper extends current Web standards towards an interoperable architecture and offers broadcasters and media application developers the possibility to easily design applications that will automatically provide a unique consistent experience across the connected devices. The architectural design is targeted to be included in the roadmap of the standards.

Technology roadmapping provides a strategic tool to help companies develop an outside-in view and challenge their current competitive perspectives. In this paper, the authors describe the roadmapping process, which is aligned, with the research and development (R&D) strategy of an applied research centre. This process is based in an adapted combination of state-of-the-art methodologies, and as a result, the case study shows interesting findings in terms of R&D strategy, technology strategy and roadmapping processes and methodology.

The application of computer-aided controversial plays resolution in sport events significantly benefits organizers, referees and audience. Nowadays, especially in ball sports, very accurate technological solutions can be found. Themain drawback of these systems is the need of complex and expensive hardware which makes them not affordable for less-known regional/traditional sports events. The lack of competitive systems with reduced hardware/software complexity and requirements motivates this research. Visual Analytics technologies permit system detecting the ball trajectory, solving with precision possible controversial plays. Ball is extracted from the video scene exploiting its shape features and velocity vector properties. Afterwards, its relative position to border line is calculated based on polynomial approximations. In order to enhance user visual experience, real-time rendering technologies are introduced to obtain virtual 3D reconstruction in quasi real-time. Comparing to other set ups, the main contribution of this work lays on the utilization of an unique camera per border line to extract 3D bounce point information. In addition, the system has no camera location/orientation limit, provided that line view is not occluded. Testing of the system has been done in real world scenarios, comparing the system output with referees' judgment. Visual results of the system have been broadcasted during Basque Pelota matches.

Context categorization is a fundamental pre-requisite for multi-domain multimedia content analysis applications. Most feature extraction methods require prior knowledge to decide if they are suitable for a specific domain and to optimize their input parameters. In this paper, we introduce a new color image context categorizationmethod (DITEC) based on the trace transform. The problem of dimensionality reduction of the obtained trace transform signal is addressed through statistical descriptors of its frequency representation that keep the underlying information. We also analyze the distortions produced by the parameters that determine the sampling of the discrete trace transform. Moreover, Feature Subset Selection (FSS) is applied to both, improve the classification performance and compact the final length of the descriptor thatwill be provided to the classifier. These extracted features offer a highly discriminant behavior for content categorization without prior knowledge requirements. The method has been experimentally validated through two different datasets.

Remote rehabilitation applications still have limited deployment. The path to achieve greater user acceptance and adherence lies in the provision of solutions in their real-life context. Such acceptance is gained through flexibility provided in terms of location, client device, interaction means, and content. This article presents a universal remote rehabilitation delivery approach supporting the introduced flexibility needs. Furthermore, an implementation of the approach in joint rehabilitation for the elderly is described. The approach has been evaluated in a real scenario within Donostia Hospital. The usability evaluation results show the validity of the approach and the acceptance of the developed human -computer interaction paradigm.

New motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation.