BROWSING POSTS BY

Christian Timmerer

Chief Innovation Officer

Prof. Dr. Christian Timmerer is the Chief Innovation Officer and a co-founder at Bitmovin. His work focuses on research and standardization in the area of adaptive video streaming, video adaptation, and Quality of Experience. He is an active member of ISO/IEC MPEG and editor for the MPEG-21, MPEG-M, MPEG-V, and MPEG-DASH standards, and thus has also a wide range of knowledge, overview, and contacts within the international technology market. He holds the position of a Full Professor for Multimedia Systems at the Alpen-Adria University Klagenfurt where he had published more than 300 papers at international conferences and journals.

gaia
Innovation

GAIA Research Project : A 3 Month Look Back

A few months ago, Bitmovin and the University of Klagenfurt announced a new collaboration on a research project called GAIA, which aims to make video streaming more sustainable. Project ‘GAIA’ is co-funded by the Austrian Research Promotion Agency (FFG) and will focus on helping the video-streaming industry reduce its carbon footprint.  Dr Christian Timmerer is…

- Bitmovin
Company News

The GAIA Research Project: Creating a Climate-Friendly Video Streaming Platform

We’re excited to share that Bitmovin and the University of Klagenfurt are collaborating on a new research project with the goal of making video streaming more sustainable. Project ‘GAIA’ is co-funded by the Austrian Research Promotion Agency (FFG) and will help enable more climate-friendly video streaming solutions by providing better energy awareness and efficiency through…

- Bitmovin
MPEG Meeting

139th MPEG Meeting Takeaways: MPEG issues Call for Evidence for Video Coding for Machines

Preface Bitmovin is a proud member and contributor to several organizations working to shape the future of video, none for longer than the Moving Pictures Expert Group (MPEG), where I along with a few senior developers at Bitmovin are active members. Personally, I have been a member and attendant of MPEG for 15+ years and…

- Bitmovin
Innovation

Efficiently Predicting Quality with ATHENA’s Video Complexity Analyzer (VCA) project

For online prediction in live streaming applications, selecting low-complexity features is critical to ensure low-latency video streaming without disruptions. For each frame/ video/ 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…

- Bitmovin
MPEG Meeting

137th MPEG Meeting Takeaways: MPEG Wins Two More Emmy® Awards

Preface Bitmovin isn’t the only organization whose sole purpose is to shape the future of video – a few senior developers at Bitmovin along with me are active members of the Moving Pictures Expert Group (MPEG). Personally, I have been a member and attendant of MPEG for 15+ years and have been documenting the progress…

- Bitmovin
Innovation

Efficient Multi-Encoding Algorithms for HTTP Adaptive Bitrate Streaming

The Future of HTTP Adaptive Streaming (HAS) According to multiple reports, video viewing will account for as much as 82% of all internet traffic by the end of 2022, as such the popularity of HTTP Adaptive Streaming (HAS) is steadily increasing to efficiently support modern demand. Furthermore, improvements in video characteristics such as frame rate,…

- Bitmovin
Innovation

ATHENA Lab: Fast Multi-Resolution and Multi-Rate Encoding for HTTP Adaptive Streaming Using Machine Learning (FaRes-ML)

The heterogeneity of the devices on the Internet and the difference among the network conditions of the users make designing a video delivery tool that can adapt to all these differences while maximizing the quality of experience (QoE) for each user a tricky problem. HTTP Adaptive Streaming (HAS) is the de-facto solution for video delivery…

- Bitmovin
Innovation

ATHENA Lab: Improving Viewer Experiences with Scalable Light Field Coding (SLFC)

Immersive Viewer Experiences with Light Field Imaging  Light field imaging is a promising technology that will provide a more immersive viewing experience. It enables some post-processing tasks like depth estimation, changing the viewport, refocusing, etc. To this end, a huge amount of data needs to be collected, processed, stored, and transmitted, which leaves the challenging…

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