Abstract: Communication networks for emergency response operations have to operate in harsh environments. As fixed infrastructures may be unavailable (e.g., they are destroyed or overloaded), mobile ad-hoc networks (MANETs) are a promising solution to establish communication for emergency response operations. However, networks for emergency responses may provide diverse connectivity characteristics which imposes some challenges, especially on routing. Routing protocols need to take transmission errors, node failures and even the partitioning of the network into account. Thus, there is a need for routing algorithms that provide mechanisms from Delay or Disruption Tolerant Networking (DTN) in order to cope with network disruptions but at the same time are as efficient as MANET routing schemes in order to preserve network resources. This paper reviews several hybrid MANET-DTN routing schemes that can be found in the literature. Additionally, the paper evaluates a realistic emergency response scenario and shows that MANET-DTN routing schemes have the potential to improve network performance as the resulting network is diverse in terms of connectivity. In particular, the network provides well-connected regions whereas other parts are only intermittently connected.

Abstract: In the medical domain it has become common to store recordings of endoscopic surgeries or procedures. The storage of these endoscopic videos provides not only evidence of the work of the surgeons but also facilitates research, the training of new surgeons and supports explanations to the patients. However, an endoscopic video archive, where tens or hundreds of new videos are added each day, needs content-based analysis in order to provide content-based search. A fundamental first step in content analysis is the segmentation of the video. We propose a new method for segmentation of endoscopic videos, based on spatial and temporal differences of motion in these videos. Through an evaluation with 20 videos we show that our approach provides reasonable performance.

Abstract: This paper proposes a framework for on-demand video streaming that enables secure and efficient delivery of data towards the end user. Our proposal requires the combined usage of three different technologies. The first one is a recent proposal by Jacobsen et al. called Content-Centric Networking (also known as Named Data Networking). It is a network architecture that introduces named data as the most valuable element in the network and divides it into so called content chunks, which are self-identifying and self-authenticating data units. The second concept we utilize derives from the approach of Dynamic Adaptive Streaming over HTTP, which allows clients to dynamically choose the quality of the received video stream according to their available resources. Finally, we adapt the concept of Broadcast Encryption to form a tool to control the access to provided content streams. The combination of these technologies enables us to design a framework that allows streaming providers to transport data to customers as dynamic adaptive encrypted content chunks, which is an efficient, flexible and scalable way of multimedia data transport.

Abstract: Social media offers an opportunity for emergency management to identify issues that need immediate reaction. To support the effective use of social media, an analysis approach is needed to identify crisis-related hotspots. We consider in this investigation the analysis of social media (i.e., Twitter, Flickr and YouTube) to support emergency management by identifying sub-events. Sub-events are significant hotspots that are of importance for emergency management tasks. Aiming at sub-event detection, recognition and tracking, the data is processed online in real-time. We introduce an incremental feature selection mechanism to identify meaningful terms and use an online clustering algorithm to uncover sub-events on-the-fly. Initial experiments are based on tweets enriched with Flickr and YouTube data collected during Hurricane Sandy. They show the potential of the proposed approach to monitor sub-events for real-world emergency situations.

Abstract: In recent years, it became common to record video footage of laparoscopic surgeries. This leads to large video archives that are very hard to manage. They often contain a considerable portion of completely irrelevant scenes which waste storage capacity and hamper an efficient retrieval of relevant scenes. In this paper we (1) define three classes of irrelevant segments, (2) propose visual feature extraction methods to obtain irrelevance indicators for each class and (3) present an extensible framework to detect irrelevant segments in laparoscopic videos. The framework includes a training component that learns a prediction model using nonlinear regression with a generalized logistic function and a segment composition algorithm that derives segment boundaries from the fuzzy frame classifications. The experimental results show that our method performs very good both for the classification of individual frames and the detection of segment boundaries in videos and enables considerable storage space savings.

Abstract: Videos of endoscopic procedures typically feature a circular content area in the image center. This area is surrounded by a dark border that carries no relevant information but is subject to noise. Thus, a considerable proportion of the available bitrate has to be wasted to encode the border regions. We propose to superimpose the border regions with a homogenous black mask so that it can be encoded efficiently with skipped macroblocks. To determine the exact position and size of the circular content area we use an efficient circle detection algorithm. Through an evaluation with 138 videos we show that the border overlay can significantly reduce the bitrate without degrading the visual quality of the content area.

Abstract: The actual content of endoscopic videos is typically limited to a circular area in the image center. This area has a dynamic position and size and is surrounded by a dark, but noisy border. In this paper we present a novel algorithm that (1) classifies which frames of an endoscopic video feature the circular content area and (2) determines its exact position and size, if present. This information is very useful for improving the performance of subsequent analysis techniques. It can also be used for more efficient video encoding and economic printing of still images in findings and reports. The evaluation shows that the proposed method is very accurate, robust and efficient in terms of runtime.

Abstract: Dynamic Adaptive Streaming over HTTP (DASH) is an ISO/IEC MPEG standard which enables the convenient and smooth transportation of multimedia data to heterogeneous end devices over networks with variable bandwidth conditions. This kind of streaming technology is mainly used with HTTP 1.0 and 1.1 respectively, which both have some drawbacks. Therefore, the IETF has started the development of HTTP 2.0, which is based on Google’s SPDY proposal and already supported by several major companies, e.g., Facebook, Twitter, Akamai, Mozilla and obviously Google. Furthermore, Content Centric Networking (CCN) is another novel approach for future networks that is considered as an revolutionary approach compared to HTTP 2.0. The CCN communication paradigm is completely different and does not rely on direct connections between hosts, it rather focuses on the content. This paper demonstrates DASH with HTTP 2.0/SPDY and CCN using our universal libdash library. Moreover, different mechanisms of DASH will be shown that can be used to provide on-demand and live content in an efficient and comfortable way.

Abstract: Multimedia delivery over the Hypertext Transfer Protocol (HTTP) is currently very popular and with MPEGs' Dynamic Adaptive Streaming over HTTP (DASH) a standard is available to provide interoperability and enable large-scale deployments using existing infrastructures (servers, proxies, caches, etc.). This paper identifies some issue when multiple DASH clients compete for a bandwidth bottleneck when transparent proxy caches are deployed. Therefore, we propose a fair share adaptation scheme to be included within the client which – through experimental results – achieve a more efficient utilization of the bottleneck bandwidth and less quality switches.

Abstract: MPEG Dynamic Adaptive Streaming over HTTP (DASH) is a new streaming standard that has been recently ratified as an international standard (IS). In comparison to other streaming systems, e.g., HTTP progressive download, DASH is able to handle varying bandwidth conditions providing smooth streaming. Furthermore, it enables NAT and Firewall traversal, flexible and scalable deployment as well as reduced infrastructure costs due to the reuse of existing Internet infrastructure components, e.g., proxies, caches, and Content Distribution Networks (CDN). Recently, the Hypertext Transfer Protocol Bis (httpbis) working group of the IETF has officially started the development of HTTP 2.0. Initially three major proposals have been submitted to the IETF i.e., Googles' SPDY, Microsofts' HTTP Speed+Mobility and Network-Friendly HTTP Upgrade, but SPDY has been chosen as working draft for HTTP 2.0. In this paper we implemented MPEG-DASH over HTTP 2.0 (i.e., SPDY), demonstrating its potential benefits and drawbacks. Moreover, several experimental evaluations have been performed that compare HTTP 2.0 with HTTP 1.1 and HTTP 1.0 in the context of DASH. In particular, the protocol overhead, the performance for different round trip times, and DASH with HTTP 2.0 in a lab test scenario has been evaluated in detail.

Abstract: Human face recognition abilities vastly outperform computer-vision algorithms working on comparable tasks, especially in the case of poor lighting, bad image quality, or partially hidden faces. In this paper, we describe a novel game with a purpose in which players must guess the name of a celebrity whose face appears blurred. The game combines a successful casual game paradigm with meaningful applications in both human- and computer-vision science. Preliminary user studies were conducted with 28 users and more than 7,000 game rounds. The results supported and extended pre-existing knowledge and hypotheses from controlled scientific experiments, which show that humans are remarkably good at recognizing famous faces, even with a significant degree of blurring. Our results will be further incorporated into research in human vision as well as machine-learning and computer-vision algorithms for face recognition.

Abstract: Video annotation is a tedious task. But especially in medical domain the knowledge of experts for the interpretation of videos is of high value. Typically medical doctors do not have time for extensive annotation, but are used to manual notes, speech recordings, and pointing. In this demo paper we present an application for annotation of medical videos, focusing on endoscopic surgery. We adopt common interaction method of medical experts to mobile computing and provide a tool for experts to annotate videos by drawing on the video and recording speech annotations.

Abstract: Dr. Aljosa Smolic joined Disney Research Zürich, Switzerland in 2009, as Senior Research Scientist and Head of the "Advanced Video Technology" group. Before he was Scientific Project Manager at the Fraunhofer Institute for Telecommunications, Heinrich- Hertz-Institut (HHI), Berlin, also heading a research group. He has been involved in several national and international research projects, where he conducted research in various fields of video processing, video coding, computer vision and computer graphics and published more than 100 refereed papers in these fields. In current projects he is responsible for research in 2D video, 3D video and free viewpoint video processing and coding.

Abstract: How to build better multimedia information systems? Management and organization of multimedia data has become easier thanks to the wide availability of metadata as well as advances in content-based image retrieval (CBIR); these advances, however, do not address what matters the most: the actual users of multimedia information systems. The goals and aims of users, i.e., their intentions, need to be put into focus in some creative way. This talk introduces the very notion of user intentions in multimedia information systems and discusses challenges and approaches in this new topic.

Abstract: Content based image retrieval has been around for some time. There are lots of different test data sets, lots of published methods and techniques, and manifold retrieval challenges, where content based image retrieval is of interest. LIRE is a Java library, that provides a simple way to index and retrieve millions of images based on the images' contents. LIRE is robust and well tested and is not only recommended by the websites of ImageCLEF and MediaEval, but is also employed in industry. This paper gives an overview on LIRE, its use, capabilities and reports on retrieval and runtime performance.

Abstract: In this paper, we present our implementation and evaluation of Dynamic Adaptive Streaming over Content centric networking (DASC) which implements MPEG Dynamic Adaptive Streaming over HTTP (DASH) utilizing a Content Centric Networking (CCN) naming scheme to identify content segments in a CCN network. In particular, video segments formatted according to MPEG-DASH are available in different quality levels but instead of HTTP, CCN is used for referencing and delivery. Based on the conditions of the network, the DASC client issues interests for segments achieving the best throughput. Due to segment caching within the network, subsequent requests for the same content can be served quicker. As a result, the quality of the video a user receives progressively improves, effectively overcoming bottlenecks in the network. We present two sets of experiments to evaluate the performance of DASC showing that throughput indeed improves. However, the generated overhead is relatively large and the adaptation strategy used for DASH that assumes an end-to-end connection could be revised for the hop-by-hop architecture of CCN.

Abstract: This paper presents the usage of CCN, which is a candidate for the next-generation Internet, in combination with the new Dynamic Adaptive Streaming over HTTP (DASH) standard, which was recently ratified by ISO/IEC MPEG. In contrast to the Internet Protocol, which is mainly based on the host-to-host connection paradigm originated in the 1970s, Content Centric Networking (CCN) focuses on the content itself, instead of its location. Considering the dominance of multimedia traffic in todays' Internet, the streaming performance of DASH over CCN as well as the problems introduced by this combination is worth to be investigated in detail. Therefore, we evaluate the protocol overhead introduced by the usage of CCN compared to the HTTP versions 1.0 and 1.1. Furthermore, the performance of DASH over CCN under different network conditions is compared to the performance of HTTP 1.0/1.1. Our results showed that although CCN comes together with higher protocol overhead than HTTP 1.0/1.1 as well as a prototype implementation, it can definitely compete with HTTP 1.0 in media streaming. Based on the evaluation results, problems as well as improvement possibilities are identified, which are the basis for future work in this area.

Abstract: This paper presents the usage of Content Centric Networking (CCN) for adaptive multimedia streaming in mobile environments, leveraging the recent ISO/IEC MPEG Dynamic Adaptive Streaming over HTTP (DASH) standard. The performance of DASH over CCN is evaluated using real-world mobile bandwidth traces and compared to previous evaluations of different DASH-based as well as proprietary systems. As there are no client-server connections in CCN, it offers the possibility to transfer data from multiple sources as well as over multiple links in parallel, which is definitely an important feature, e.g., for mobile devices offering multiple network links. This functionality is used and evaluated in this paper in combination with DASH, making it possible to dynamically choose the best performing link for media streaming, which is a clear advantage over DASH using HTTP and the TCP/IP protocol stack. The evaluation therefore investigates DASH over CCN in two scenarios using synthetic and real-world mobile bandwidth traces respectively, showing a significantly better performance than conventional DASH using only one connection.

Abstract: The delivery of multimedia content over HTTP and on top of existing Internet infrastructures is becoming the preferred method within heterogeneous environment. The basic design principle is having an intelligent client which selects given and applicable media representations by issuing HTTP requests for individual segments based on the users' context and current conditions. Typically, this client behavior differs between implementations of the same kind and for the objective evaluations thereof appropriate datasets are needed. This paper presents a distributed dataset for the recently published MPEG-DASH standard which is mirrored at different sites across Europe, namely Klagenfurt, Paris, and Prague. A client implementation may choose to request segments from these sites and dynamically switch to a different location, e.g., in case the one currently used causes any issues. Thus, this distributed DASH dataset can be used for real-world evaluations enabling the simulation of switching between different content delivery networks.

Abstract: MPEG-M is a suite of ISO/IEC standards (ISO/IEC 23006) that has been developed under the auspices of Moving Picture Experts Group (MPEG). MPEG-M, also known as Multimedia Service Platform Technologies (MSPT), facilitates a collection of multimedia middleware APIs and elementary services as well as service aggregation so that service providers can offer users a plethora of innovative services by extending current IPTV technology toward the seamless integration of personal content creation and distribution, e-commerce, social networks and Internet distribution of digital media.