Head-worn adaptive display

An eyepiece includes a mechanical frame adapted to secure a lens and an image source facility above the lens. The image source facility includes an LED, a planar illumination facility and a reflective display. The planar illumination facility converts a light beam from the LED received on a side of the planar illumination facility into a top emitting planar light source, uniformly illuminates the reflective display, and is substantially transmissive to allow reflected light to pass through towards a beam splitter. The beam splitter is positioned to receive the image light and to reflect a portion onto a mirrored surface. The mirrored surface is positioned and shaped to reflect the image light into an eye of a user of the eyepiece thereby providing an image within a field of view, the mirrored surface further adapted to be partially transmissive within an area of image reflectance.

Eyepiece with uniformly illuminated reflective display

Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the large number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and even more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL and NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to practitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities in the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling, and security related capabilities. Features driving the ability to scale read requests and write requests, or scaling data storage are investigated, in particular partitioning, replication, consistency, and concurrency control. Furthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and the suitability of various solutions for different sets of applications is examined. Consequently, this study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages.

/pdf/data-management-in-cloud-environments-nosql-and-newsql-data-l9mwpy11ek.pdf

Data management in cloud environments: NoSQL and NewSQL data stores

See-through display with an optical assembly including a wedge-shaped illumination system

More and more people read the news online, e.g., by visiting the websites of their favorite newspapers or by navigating the sites of news aggregators. However, the abundance of news information that is published online every day through different channels can make it challenging for readers to locate the content they are interested in. The goal of News Recommender Systems (NRS) is to make reading suggestions to users in a personalized way. Due to their practical relevance, a variety of technical approaches to build such systems have been proposed over the last two decades. In this work, we review the state-of-the-art of designing and evaluating news recommender systems over the last ten years. One main goal of the work is to analyze which particular challenges of news recommendation (e.g., short item life times and recency aspects) have been well explored and which areas still require more work. Furthermore, in contrast to previous surveys, the paper specifically discusses methodological questions and today’s academic practice of evaluating and comparing different algorithmic news recommendation approaches based on accuracy measures.

News recommender systems – Survey and roads ahead

Since broadband network connections are becoming ubiquitous, people expect access to multimedia content anywhere anytime. This new demand results in a need to create and develop new, powerful devices for multimedia consumption. The new devices, each having their set Of network and terminal capabilities, allow transparent access to multimedia and therefore open the path to transparent mobility of multimedia. In this paper we demonstrate how MPEG-21 can be used to provide a solution for session mobility between devices with different terminal and network capabilities. We demonstrate how MPEG-21 Digital Items call be used for realizing session mobility between two different devices and how it can overcome the difficulties of capability differences. The feasibility, of the MPEG-21 approach for session mobility is illustrated by the implementation of a demonstrator on the Windows Mobile 2003 and Windows XP platforms. This paper outlines the technical details of the implementation and the results of several performance measurements on both platforms.

MPEG-21 session mobility on mobile devices

An optimized MPEG-21 BSDL framework for the adaptation of scalable bitstreams

Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%.

/pdf/lightweight-object-tracking-in-compressed-video-streams-248joyt6b1.pdf

Lightweight object tracking in compressed video streams demonstrated in region-of-interest coding

Three low complexity algorithms that allow spatial scalability in the context of video coding are presented in this paper. We discussed the feasibility of reusing motion and residual texture information of the base layer in the enhancement layer. The prediction errors that arise from the discussed filters and schemes are evaluated in terms of the Mean of Absolute Differences. For the interpolation of the decoded pictures from the base layer, the presented 6-tap and bicubic filters perform significantly better than the bilinear and nearest neighbor filters. In contrast, when reusing the motion vector field and the error pictures of the base layer, the bilinear filter performs best for the interpolation of residual texture information. In general, reusing the motion vector field and the error pictures of the base layer gives the lowest prediction errors. However, our tests showed that for some sequences that have regions with complex motion activity, interpolating the decoded picture of the base layer gives best result. This means that an encoder should compare all possible prediction schemes combined with all interpolation filters in order to achieve optimal prediction. Obviously this would not be possible for real-time content creation.

Comparison of prediction schemes with motion information reuse for low complexity spatial scalability

Digital file-based libraries for the audio-visual material of television broadcasters and production houses are becoming desirable. These libraries not only address the problem of loss of content due to tape deterioration, but also improve disclosure of the content. However, switching to a digital file-based library involves many new concerns and problems for content providers. This paper will discuss one of them, namely the metadata. Metadata is additional information that is required in order to be able to search, retrieve, and play out the stored content. Different standards for metadata are currently available, each having its own field of application and characteristics. In this paper, we introduce an objective framework that one can use in order to select the appropriate metadata standard for its particular type of application. This framework is applied to four well-known metadata standards, namely Dublin Core, MPEG-7, P/Meta, and SMEF.

Evaluation of metadata standards in the context of digital audio-visual libraries

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