The 5th Annual Lifelog Search Challenge (LSC 2022), co-organized by Klaus Schöffmann, will be this year’s grand challenge at the ACM International Conference on Multimedia Retrieval (ICMR 2022) in Newark, NJ, USA. More information here: https://www.icmr2022.org/program/challenges/
Klaus Schöffmann will give an invited talk about Relevant Content Detection in Cataract Surgery Videos at the IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA) on April 19, 2022, in Salzburg, Austria. More information here: https://ipta-conference.com/ipta22/index.php/invited-speakers
Klaus Schöffmann will give a tutorial about Medical Video Processing at the IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA) on April 19, 2022, in Salzburg, Austria. More information here: https://ipta-conference.com/ipta22/index.php/invited-speakers
We are happy that our 2nd International Workshop on Interactive Multimedia Retrieval (IMuR) has been accepted for the ACM Multimedia Conference 2022 (ACMMM) in Lisbon, Portugal. More information can be found here: https://sites.google.com/view/imur2022
Babak Taraghi (Alpen-Adria-Universität Klagenfurt), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt).
Abstract: There exist many applications that produce multimedia traffic over the Internet. Video streaming is on the list, with a rapidly growing desire for more bandwidth to deliver higher resolutions such as Ultra High Definition (UHD) 8K content. HTTP Adaptive Streaming (HAS) technique defines baselines for audio-visual content streaming to balance the delivered media quality and minimize streaming session defects. On the other hand, video codecs development and standardization help the theorem by introducing efficient algorithms and technologies. Versatile Video Coding (VVC) is one of the latest advancements in this area that is still not fully optimized and supported on all platforms. Stated optimization and supporting many platforms require years of research and development. This paper offers a dataset that facilitates the research and development of the aforementioned technologies. Our open-source dataset comprises Dynamic Adaptive Streaming over HTTP (MPEG-DASH) multimedia test assets of encoded Advanced Video Coding (AVC), High Efficiency Video Coding (HEVC), AOMedia Video 1 (AV1), and VVC content with resolutions of up to 7680×4320 or 8K. Our dataset has a maximum media duration of 322 seconds, and we offer our MPEG-DASH packaged content with two segments lengths, 4 and 8 seconds.
The dataset is available here.
June 14–17, 2022 | Athlone, Ireland
Vignesh V Menon (Alpen-Adria-Universität Klagenfurt), Christian Feldmann (Bitmovin, Klagenfurt), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt),
Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt).
Abstract:
VCA in content-adaptive encoding applications
For online analysis of the video content complexity in live streaming applications, selecting low-complexity features is critical to ensure low-latency video streaming without disruptions. To this light, for each video (segment), two features, i.e., the average texture energy and the average gradient of the texture energy, are determined. A DCT-based energy function is introduced to determine the block-wise texture of each frame. The spatial and temporal features of the video (segment) are derived from the DCT-based energy function. The Video Complexity Analyzer (VCA) project aims to provide an
efficient spatial and temporal complexity analysis of each video (segment) which can be used in various applications to find the optimal encoding decisions. VCA leverages some of the x86 Single Instruction Multiple Data (SIMD) optimizations for Intel CPUs and
multi-threading optimizations to achieve increased performance. VCA is an open-source library published under the GNU GPLv3 license.
Github: https://github.com/cd-athena/VCA
Online documentation: https://cd-athena.github.io/VCA/
On April 6th, 2022, Natalia Mathá (former Sokolova) successfully defended her thesis on “Relevance Detection and Relevance-Based Video Compression in Cataract Surgery Videos” under the supervision of Assoc.-Prof. Klaus Schöffmann and Assoc.-Prof. Christian Timmerer. The defense was chaired by Univ.-Prof. Hermann Hellwagner and the examiners were Assoc.-Prof. Konstantin Schekotihin and Assoc.-Prof. Mathias Lux. Congratulations to Dr. Mathá for this great achievement!
The 13th ACM Multimedia Systems Conference (ACM MMSys 2022)
June 14–17, 2022 | Athlone, Ireland
Reza Shokri Kalan (Digiturk Company, Istanbul), Reza Farahani (Alpen-Adria-Universität Klagenfurt), Emre Karsli (Digiturk Company, Istanbul), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)
Over-the-Top (OTT) service providers need faster, cheaper, and Digital Rights Management (DRM)-capable video streaming solutions. Recently, HTTP Adaptive Streaming (HAS) has become the dominant video delivery technology over the Internet. In HAS, videos are split into short intervals called segments, and each segment is encoded at various qualities/bitrates (i.e., representations) to adapt to the available bandwidth. Utilizing different HAS-based technologies with various segment formats imposes extra cost, complexity, and latency to the video delivery system. Enabling an integrated format for transmitting and storing segments at Content Delivery Network (CDN) servers can alleviate the aforementioned issues. To this end, MPEG Common Media Application Format (CMAF) is presented as a standard format for cost-effective and low latency streaming. However, CMAF has not been adopted by video streaming providers yet and it is incompatible with most legacy end-user players. This paper reveals some useful steps for achieving low latency live video streaming that can be implemented for non-DRM sensitive contents before jumping to CMAF technology. We first design and instantiate our testbed in a real OTT provider environment, including a heterogeneous network and clients, and then investigate the impact of changing format, segment duration, and Digital Video Recording (DVR) window length on a real live event. The results illustrate that replacing the transport stream (.ts) format with fragmented MP4 (.fMP4) and shortening segments’ duration reduces live latency significantly.
Keywords: HAS, DASH, HLS, CMAF, Live Streaming, Low Latency
