Abstract: Multimedia is ubiquitously available online with large amounts of video increasingly consumed through Web sites such as YouTube or Google Video. However, online multimedia typically limits users to visual/auditory stimulus, with onscreen visual media accompanied by audio. The recent introduction of MPEG-V proposed multi-sensory user experiences in multimedia environments, such as enriching video content with so-called sensory effects like wind, vibration, light, etc. In MPEG-V, these sensory effects are represented as Sensory Effect Metadata (SEM), which is additionally associated to the multimedia content. This paper presents three user studies that utilize the sensory effects framework of MPEG-V, investigating the emotional response of users and enhancement of Quality of Experience (QoE) of Web video sequences from a range of genres with and without sensory effects. In particular, the user studies were conducted in Austria and Australia to investigate whether geography and cultural differences affect users’ elicited emotional responses and QoE.

Abstract: Nowadays video is an important part of the Web and Web sites like YouTube, Hulu, etc. count millions of users consuming their content every day. However, these Web sites mainly use media players based on proprietary browser plug-ins (i.e., Adobe Flash) and do not leverage adaptive streaming systems. This paper presents a seamless integration of the recent MPEG standard on Dynamic Adaptive Streaming over HTTP (DASH) in the Web using the HTML5 video element. Therefore, we present DASHJS, a JavaScript-based MPEG-DASH client which adopts the Media Source API of Google’s Chrome browser to present a flexible and potentially browser independent DASH client. Furthermore, we present the integration of WebM based media segments in DASH giving a detailed description of the used container format structure and a corresponding Media Presentation Description (MPD). Our preliminary evaluation demonstrates the bandwidth adaption capabilities to show the effectiveness of the system.

Abstract: We evaluate the performance of several routing protocols for mobile ad-hoc networks (MANETs) in an emergency response scenario. The simulated scenario uses a disaster area mobility model and a wireless shadowing model to represent realistic first responder movements in a hybrid indoor/outdoor environment. The resulting scenario imposes some challenges on the MANET routing protocols such as intermittent connectivity and network partitions. The simulation results show that nodes have diverse connectivity characteristics which are challenging for state-of-the-art MANET routing protocols.

Abstract: This paper presents a new method for estimating the level of service (LOS) on motorways in the compressed video domain. The method performs statistical computations on motion vectors of MPEG4 encoded video streams within a predefined region of interest to determine a set of four motion features describing the speed and density of the traffic stream. These features are fed into a Gaussian radial basis function network to classify the corresponding LOS. To improve the classification results, vectors of moving objects are clustered and outliers are eliminated. The proposed method is designed to be executed on a server system, where a large number of camera live streams can be analyzed in parallel in real-time. Evaluations with a comprehensive set of real-world training and test data from an Austrian motorway have shown an average accuracy of 86.7% on the test data set for classifying all four LOS levels. With a mean execution time of 48 microseconds per frame on a common server, hundreds of video streams can be analyzed in real-time.

Abstract: We demonstrate our novel video-based real-time traffic event notification and verification system LOOK2. It generates fast and reliable traffic information about relevant traffic state and road conditions changes on observed roads. It utilizes installed road-side sensors providing low-level traffic and environmental data, as well as video sensors which gain high-level traffic information from live video analysis. Spatio-temporal data fusion is applied on all available traffic and environmental data to gain reliable traffic information. This traffic information is published by a DATEXII compliant web service to a web-based traffic desk application. Road network and traffic channel operators receive real-time and relevant traffic event notifications by using this application. The system also enables a visual verification of the notified situations.

Abstract: This paper presents a novel method for video-based traffic state detection on motorways performed on smart cameras. Camera calibration parameters are obtained from the known length of lane markings. Mean traffic speed is estimated from Kanade-Lucas-Tomasi (KLT) optical flow method using a robust outlier detection. Traffic density is estimated using a robust statistical counting method. Our method has been implemented on an embedded smart camera and evaluated under different road and illumination conditions. It achieves a detection rate of more than 95% for stationary traffic.

Abstract: Social media are becoming an important instrument for supporting crisis management, due to their broad acceptance and the intensive usage of mobile devices for accessing them. Social platforms facilitate collaboration among the public during a crisis and also support after-the-fact analysis. Thus, social media are useful for the processes of understanding, learning, and decision making. In particular, having information from social networks in a suitable, ideally summarized, form can speed up such processes. The present study relies on Flickr and YouTube as social media and aims at automatically identifying individual sub-events within a crisis situation. The study applies a two-phase clustering approach to detect those sub-events. The first phase uses geo-referenced data to locate a sub-event, while the second phase uses the natural language descriptions of pictures and videos to further identify the ”what-about” of those sub-events. The results show high potential of this social media-based clustering approach for detecting crisis-related sub-events.

Abstract: Social networks give the opportunity to gather and share knowledge about a situation of relevance. This so called user-generated content is getting increasingly important during crisis management. It facilitates the collaboration with citizens or parties involved from the very beginning of the crisis. The information captured in form of images, text or videos is a valuable source of identifying sub-events of a crisis. In this study, we use metadata of images and videos collected from Flickr and YouTube to extract sub-events in crisis situations. We investigate the suitability of clustering techniques to detect sub-events. In particular two algorithms are evaluated on several data sets related to crisis situations. The results show the high potential of the approach proposed.

Abstract: Emergency management is about assessing critical situations, followed by decision making as a key step. Clearly, information is crucial in this two-step process. The technology of social (multi)media turns out to be an interesting source for collecting information about an emergency situation. In particular, situational information can be captured in form of pictures, videos, or text messages. The present paper investigates the application of multimedia metadata to identify the set of sub-events related to an emergency situation. The used metadata is compiled from Flickr and YouTube during an emergency situation, where the identification of the events relies on clustering. Initial results presented in this paper show how social media data can be used to detect different sub-events in a critical situation.

Abstract: This paper demonstrates a novel 3D Video Browser (3VB) that enables interactive search within a single video as well as video collections by utilizing 3D projection and an intuitive interaction. The browsing approach is based on hierarchical search, which means that the user can split a video into several segments. The 3VB disposes a convenient interface that allows flexible arrangement of video segments in the 3D space. It allows for concurrent playback of video segments and flexible inspection of these segments at any desired level of detail through convenient user interaction.

Abstract: Dynamic Adaptive Streaming over HTTP (DASH) is a convenient approach to transfer videos in an adaptive and dynamic way to the user. As a consequence, this system provides high bandwidth flexibility and is especially suitable for mobile use cases where the bandwidth variations are tremendous. In this paper we have integrated the Scalable Video Coding (SVC) extensions of the Advanced Video Coding (AVC) standard into the recently ratified MPEG-DASH standard. Furthermore, we have evaluated our solution under restricted conditions using bandwidth traces from mobile environments and compared it with an improved version of our MPEG-DASH implementation using AVC as well as major industry solutions.

Abstract: MPEGs' Dynamic Adaptive Streaming over HTTP (MPEG-DASH) is an emerging standard designed for media delivery over the top of existing infrastructures and able to handle varying bandwidth conditions during a streaming session. This requirement is very important, specifically within mobile environments and, thus, DASH could potentially become a major driver for mobile multimedia streaming. Hence, this paper provides a detailed evaluation of our implementation of MPEG DASH compared to the most popular propriety systems, i.e., Microsoft Smooth Steaming, Adobe HTTP Dynamic Streaming, and Apple HTTP Live Streaming. In particular, these systems will be evaluated under restricted conditions which are due to vehicular mobility. In anticipation of the results, our prototype implementation of MPEG-DASH can very well compete with state-of-the-art solutions and, thus, can be regarded as a mature standard ready for industry adaption.

Abstract: Multimedia streaming technologies based on the Hypertext Transfer Protocol (HTTP) are very popular and used by many content providers such as Netflix, Hulu, and Vudu. Recently, ISO/IEC MPEG has ratified Dynamic Adaptive Streaming over HTTP (DASH) which extends the traditional HTTP streaming with an adaptive component addressing the issue of varying bandwidth conditions that users are facing in networks based on the Internet Protocol (IP). Additionally, industry has already deployed several solutions based on such an approach which simplifies large scale deployment because the whole streaming logic is located at the client. However, these features may introduce drawbacks when multiple clients compete for a network bottleneck due to the fact that the clients are not aware of the network infrastructure such as proxies or other clients. This paper identifies these negative effects and the evaluation thereof using MPEG-DASH and Microsoft Smooth Streaming. Furthermore, we propose a novel adaptation algorithm introducing the concept of fairness regarding a cluster of clients. In anticipation of the results we can conclude that we achieve more efficient bottleneck bandwidth utilization and less quality switches.

Abstract: Adaptive HTTP streaming got lot of attention in recent years and with dynamic adaptive streaming over HTTP (DASH) a standard is available. Many papers cover this topic and present their research results, but unfortunately all of them use their own private dataset which – in most cases – is not publicly available. Hence, it is difficult to compare, e.g., adaptation algorithms in an objective way due to the lack of a common dataset which shall be used as basis for such experiments. In this paper, we present our DASH dataset featuring our DASHEncoder, an open source DASH content generation tool. We also provide basic evaluations of the different segment lengths, the influence of HTTP server settings, and, in this context, we show some of the advantages as well as problems of shorter segment lengths.

Abstract: Manual image annotation is a tedious and time-consuming task, while automated methods are error prone and limited in their results. Human computation, and especially games with a purpose, have shown potential to create high quality annotations by "hiding the complexity" of the actual annotation task and employing the "wisdom of the crowds". In this demo paper we present two games with a single purpose: finding regions in images that correspond to given terms. We discuss approach, implementation, and preliminary results of our work and give an outlook to immediate future work.

Abstract: In this paper we demonstrate our MPEG-DASH evaluation suite, which comprises several components on the client side as well as on the server side. The major client components are the VLC DASH plugin, libDASH, and DASH-JS, a JavaScript-based DASH client. These tools enable performance tests on various platforms, e.g., Windows and Linux as well as mobile platforms such as Android. Moreover, due to their flexible structure it is possible to integrate adaptation logics and evaluate them under consistent conditions. On the server side we provide the content generation tool DASHEncoder, our MPEG-DASH datasets well as the MPEG-DASH conformance validator.

Abstract: This paper presents our peer-assisted Dynamic Adaptive Streaming over HTTP (pDASH) proposal as well as an evaluation based on our DASH simulation environment in comparison to conventional approaches, i.e., non-peer-assisted DASH. Our approach maintains the standard conformance to MPEG-DASH enabling an easy and straightforward way of enhancing a streaming system with peer assistance to reduce the bandwidth and infrastructure requirements of the content/service provider. In anticipation of the results our system achieves a bandwidth reduction of Content Distribution Networks (CDN) and as a consequence the corresponding infrastructure costs of the content/service providers by up to 25% by leveraging the upstream capacity of neighboring peers. Furthermore, the cost savings have been evaluated using a cost model that is based on the current Amazon CloudFront pricing scheme. Furthermore, we have also evaluated the performance impact that various combinations of quality levels of the content could have in a peer-assisted streaming system as well as the client behavior in such an environment.

Abstract: Content-based retrieval systems leverage low level features such as color, texture or local information of images to find similar images to a respective query image. In recent years the Bag of Visual Words (BoVW) approach, which relies on quantized visual information around local image patches, has gained importance in image retrieval. In this paper we focus on fuzzy algorithms, in order to improve the descriptiveness of image descriptors. We extend the BoVW approach by applying fuzzy clustering and fuzzy assignment to take a step towards more effective visual descriptors, which are matched against each other in content-based similarity searches.

Abstract: HTTP streaming has gained significant attraction in the last few years. Currently many commercial as well as standardized streaming systems are already offering adaptive streaming. In most cases, the adaptation is achieved by switching between separately encoded video streams in different qualities. In contrast to that, this paper focuses on the applicability of scalable video coding based on the H.264/SVC standard for adaptive HTTP streaming. Recent work has already highlighted the conceptual advantages like better cache utilization, fine-grained bit rate scalability, and lower storage requirements. This paper discusses the actual realization and design options for implementing priority streaming using the ISO Base Media File Format (BMFF). We propose three different strategies for organizing the scalable video bit stream that consider both the possibilities as well as limitations of the ISO BMFF. The proposed strategies are discussed and evaluated both conceptually and quantitatively. For that purpose, we provide a detailed analysis based on modeling both the overhead of the file format and the HTTP encapsulation. The results for all three priority streaming strategies show that the limitations of the ISO BMFF result in a high relative overhead in the case of low bit rate content. However, when applied to high quality content, priority streaming of H.264/SVC can be implemented at a very low cost. Depending on the number of layers and the offered scalability dimensions, different strategies should be chosen to minimize the overhead. Based on the analytical model and the discussion, this paper provides guidance for selecting the most efficient strategy.