Dynamic Adaptive Point Cloud Streaming

High-quality point clouds have recently gained interest as an emerging form of representing immersive 3D graphics. Unfortunately, these 3D media are bulky and severely bandwidth intensive, which makes it difficult for streaming to resource-limited and mobile devices. This has called researchers to propose efficient and adaptive approaches for streaming of high-quality point clouds. In this paper, we run a pilot study towards dynamic adaptive point cloud streaming, and extend the concept of dynamic adaptive streaming over HTTP (DASH) towards DASH-PC, a dynamic adaptive bandwidth-efficient and view-aware point cloud streaming system. DASH-PC can tackle the huge bandwidth demands of dense point cloud streaming while at the same time can semantically link to human visual acuity to maintain high visual quality when needed. In order to describe the various quality representations, we propose multiple thinning approaches to spatially sub-sample point clouds in the 3D space, and design a DASH Media Presentation Description manifest specific for point cloud streaming. Our initial evaluations show that we can achieve significant bandwidth and performance improvement on dense point cloud streaming with minor negative quality impacts compared to the baseline scenario when no adaptations is applied.Comment: 6 pages, 23rd ACM Packet Video (PV'18) Workshop, June 12--15, 2018, Amsterdam, Netherland

Wohnen “in Goyas letztem Raum”: Eine intermediale Poetik des Entsetzens. Die Zitierung von Goyas Pinturas Negras in Ingeborg Bachmanns Roman Malina. [Living in “Goya’s Last Room”. An Intermedial Poetics of Dread. Ingeborg Bachmann’s use of Goya’s Pinturas Negras in her novel Malina]

Ingeborg Bachmann’s recurrent references to the Spanish painter Francisco de Goya have frequently been noted, but have so far never been investigated. After outlining, in chapter one, Bachmann’s references to Goya in her thesis on Wittgenstein as well as in the Franza-Fragment and in her only novel Malina, this thesis sets out to highlight the text-image relation between Bachmann’s novel Malina and Goya’s series of murals which are known as the so called „Black Paintings“. Chapter two focuses on the importance of intertextuality and intermediality in Bachmann’s novel and the importance of quotation for the female narrator, who relies on intertextual and intermedial references to express her traumatic experiences. After an introduction into the aesthetics of Goya, in chapter three, chapters four and five examine the text-image relation between Goya’s painting El Perro Semihundido and the first chapter in Bachmann’s novel. The double perspective contained in El Perro, of the subjective expression of the dog’s longing for rescue and the objective futility of this hope as expressed by the dog’s positioning against the abstract background setting, is transferred onto the female narrator and her longing to be rescued through love. Chapter five especially focuses on the (problematic) semantic shifts which occur in the course of this transformation from an abstract representation in the painting to the depiction of concrete and personalized experiences in the text. Chapter six investigates the correlations between Bachmann’s dream chapter and the aesthetics of Goya’s murals, and asks to what extent Bachmann succeeds in transferring the main motifs in Goya’s images into literary form. Chapter seven explores the similarities and media-specific differences in the strategies deployed for depicting madness, violence and destruction in Bachmann’s text and in Goya’s murals and his series of prints on the Desasters of War. Bachmann’s novel Malina shows an extraordinary richness in intertextual and intermedial references. Analysing the explicit as well as implicit references to Goya’s late works in the novel this thesis addresses one area on Ingeborg Bachmann which has not been researched in detail so far

Scalable Video Coding Guidelines and Performance Evaluations for Adaptive Media Delivery of High Definition Content

International audienceScalability within media coding allows for content adaptation towards heterogeneous user contexts and enables in-network adaptation. However, there is no straightforward solution how to encode the content in a scalable way while maximizing rate-distortion performance. In this paper we provide encoding guidelines for scalable video coding based on a survey of media streaming industry solutions and a comprehensive performance evaluation using four state of the art scalable video codecs with a focus on high-definition content (1080p)

Innovation Mashups: Academic Rigor Meets Social Networking Buzz

Exploring new options for publishing and content delivery offers an enormous opportunity to improve the state of the art and further modernize academic and professional publications. Traditional organizations such as the IEEE Computer Society, ACM, and Usenix have been encountering increasing competition from new ways of rapid publishing and dissemination, including social networking sites (Facebook, Twitter, LinkedIn, Google+), blogs with enabled commenting, video posting (YouTube), Slashdot, and many other types of media. Liking is replacing traditional impact factors, comments left on authors\u27 webpages or blogs are replacing formal reviews, and site visits have more relevance than the number of article citations

Bitrate Ladder Prediction Methods for Adaptive Video Streaming: A Review and Benchmark

HTTP adaptive streaming (HAS) has emerged as a widely adopted approach for over-the-top (OTT) video streaming services, due to its ability to deliver a seamless streaming experience. A key component of HAS is the bitrate ladder, which provides the encoding parameters (e.g., bitrate-resolution pairs) to encode the source video. The representations in the bitrate ladder allow the client's player to dynamically adjust the quality of the video stream based on network conditions by selecting the most appropriate representation from the bitrate ladder. The most straightforward and lowest complexity approach involves using a fixed bitrate ladder for all videos, consisting of pre-determined bitrate-resolution pairs known as one-size-fits-all. Conversely, the most reliable technique relies on intensively encoding all resolutions over a wide range of bitrates to build the convex hull, thereby optimizing the bitrate ladder for each specific video. Several techniques have been proposed to predict content-based ladders without performing a costly exhaustive search encoding. This paper provides a comprehensive review of various methods, including both conventional and learning-based approaches. Furthermore, we conduct a benchmark study focusing exclusively on various learning-based approaches for predicting content-optimized bitrate ladders across multiple codec settings. The considered methods are evaluated on our proposed large-scale dataset, which includes 300 UHD video shots encoded with software and hardware encoders using three state-of-the-art encoders, including AVC/H.264, HEVC/H.265, and VVC/H.266, at various bitrate points. Our analysis provides baseline methods and insights, which will be valuable for future research in the field of bitrate ladder prediction. The source code of the proposed benchmark and the dataset will be made publicly available upon acceptance of the paper