Immersive video applications impose unpractical bandwidth requirements for best-effort networks. With Multi-View (MV) streaming, these can be minimized by resorting to view prediction techniques. SmoothMV is a multi-view system that uses a non-intrusive head tracking mechanism to detect the viewer's interest and select appropriate views. By coupling Neural Networks (NNs) to anticipate the viewer's interest, a reduction of view-switching latency is likely to be obtained. The objective of this paper is twofold: 1) Present a solution for acquisition of gaze data from users when viewing MV content; 2) Describe a dataset, collected with a large-scale testbed, capable of being used to train NNs to predict the user's viewing interest. Tracking data from head movements was obtained from 45 participants using an Intel Realsense F200 camera, with 7 video playlists, each being viewed a minimum of 17 times. This dataset is publicly available to the research community and constitutes an important contribution to reducing the current scarcity of such data. Tools to obtain saliency/heat maps and generate complementary plots are also provided as an open-source software package.

Multimedia content production is nowadays widespread due to technological advances, namely supported by smartphones and social media. Although the massive amount of media content brings new opportunities to the industry, it also obfuscates the relevance of marketing content, meant to maintain and lure new audiences. This leads to an emergent necessity of producing these kinds of contents as quickly and engagingly as possible. Creating these automatically would decrease both the production costs and time, particularly by using static media for the creation of short storytelling animated clips. We propose an innovative approach that uses context and content information to transform a still photo into an appealing context-aware video clip. Thus, our solution presents a contribution to the state-of-the-art in computer vision and multimedia technologies and assists content creators with a value-added service to automatically build rich contextualized multimedia stories from single photographs.

The overtaking maneuver can be often dangerous and risky, especially when driving in rural roads, with a significant probability of leading to fatalities and serious injuries. Vehicle communication emerges as one of the leading technologies to improve the driving experience and road safety. This article presents a system designed to augment road safety in an Over-taking Maneuver, providing the ahead vehicle's Line-of-Sight by real-time video-streaming. It uses the C-V2X Transmission Mode 4 that, building upon cellular technology, has evolved as one of the main standards for vehicle communication. Results show an effective application of the system in real overtaking scenarios, enhancing the safety and proving its usefulness. Whilst having some impact on the latency, the solution incurred in low packet losses and provided good video quality.

Technological advances are pushing into the mass market innovative wearable devices featuring increasing processing and sensing capacity, non-intrusiveness and ubiquitous use. Sensors built-in those devices, enable acquiring different types of data and by taking advantage of the available processing power, it is possible to run intelligent applications that process the sensed data to offer added-value to the user in multiple domains. Although not new to the modern society, it is unquestionable that the present exercise boom is rapidly spreading across all age groups. However, in a great majority of cases, people perform their physical activity on their own, either due to time or budget constraints and may easily get discouraged if they do not see results or perform exercises inadequately. This paper presents an application, running on a wearable device, aiming at operating as a personal trainer that validates a set of proposed exercises in a sports session. The developed solution uses inertial sensors of an Android Wear smartwatch and, based on a set of pattern recognition algorithms, detects the rate of success in the execution of a planned workout. The fact that all processing can be executed on the device is a differentiator factor to other existing solutions.

Context Recognition is an important element for developing context aware mobile applications. However, context is mostly available as low-level sensor data that are in form not suitable for mobile applications. In this paper, we present a process that uses classifiers for recognizing high-level contexts from low-level sensor data. The process demonstrates accurate recognition of user activity contexts, using smart-phone built-in sensors. We describe and illustrate our context recognition model and then demonstrate its application in a context aware mobile multimedia recommendation system.

This paper addresses the inter-operability problem of multimedia terminal in media content delivery over heterogeneous networks and devices. We design and implement a terminal which includes a content browser providing presentation, navigation and interaction with MPEG-21 Digital Item Declaration (MPEG-21 DID) in order to support universal media access (UMA). We optimized the architecture in a client-server distributed approach with Web Service support. This terminal enables the MPEG-21 standard compliant content accessible on different terminal devices via common Web browsers. Such a design strategy illustrates a next-generation multimedia terminal supporting inter-operability in multimedia content adaptation over a heterogeneous delivery chain.

This paper addresses multimedia end user system design for content distribution over heterogeneous networks and terminals, with particular focus on end-to-end quality of service (QoS) control. A multimedia terminal comprising content-related metadata processor, usage environment characteristics provider, end user QoS monitor and H.264psilas extension scalable video coding (SVC) audio-visual player in coordination under a terminal middleware, has been conceived and implemented. This end user terminal enables end-to-end QoS control for content adaptation solution both in semantic and physical approaches to maximize end userpsilas perceptual experience and minimize resources. Such design approach illustrates a possible architecture for next generation multimedia end user terminal supporting MPEG-21 and H.264psilas extension SVC codec standards.

This paper proposes a framework for a virtual classroom application based on a Virtual Collaboration System (VCS), which is being developed under the VISNET II Network of Excellence (NoE)1, and discusses adaptation technologies that enable seamless access to classroom sessions while intellectual property and digital rights are managed. The proposed virtual classroom framework enables academic institutions to conduct their collaborative lecture series, to which registered students will be able to attend remotely and interactively over the Internet. Furthermore, the general public may also follow the classroom sessions under certain restrictions imposed by the participating institutions. In order to facilitate seamless access to a heterogeneous audience that is composed of users with various preferences and privileges accessing the classroom sessions over different network infrastructures and using terminal devices with diverse capabilities, context-aware content adaptation is required to meet constraints imposed by the usage context and enhance the quality of the user experience. Thus, this paper describes the concepts and functionalities of a context-aware content adaptation platform that suits the requirements of such multimedia application scenarios. This platform is able to consume low-level contextual information to infer higher-level contexts, and thus decide the need for and type of adaptation operations to be performed upon the content. In this way, it is aimed to meet usage constraints while also satisfying restrictions imposed by the Digital Rights Management (DRM) to govern the use of protected content.