About
In 2015 joined as a Research Fellow the Visual Information Laboratory, led by Prof David R. Bull, within the Department of Electrical and Electronic Engineering, University of Bristol, UK. I received my Ph.D. in July 2014 from the Department of Computer Science and Engineering, University of Ioannina, Greece, under the guidance of Prof Lisimachos P. Kondi . My main research interests include topics around the video processing pipeline: acquisition, analysis, compression, and communication, as detailed below. Other side research activities include data and biomedical engineering.Research Areas
- Video Coding & Streaming
- Standard and Immersive (HDR/HFR/360°/Volumetric) video coding
- Optimisation of Video Encoding for Adaptive Streaming
- Creating Databases
- Deep-Learning based Analysis and Coding
- Sustainable Creative Technologies
- Energy Profiling of Video Production Workflows
- Design of Energy Efficient Video Technologies and Communication
- Reduced Complexity in Creative Technologies
- Visual Quality Assessment & Experience
- Full reference/reduce/no reference metrics
- Content-specific design of metrics (pristine/UGC/transcoded/low-light content)
- Novel subjective quality assessment and experience tools and methods
- Perceptual Video Coding
- Content-aware compression
- Perceptually aligned parameter selection
- Rate quality optimisation
News & Activities
- May 2021: Journal Paper accepted in Special Issue "Applied Artificial Intelligence and Machine Learning for Video Coding and Streaming", IEEE Open Journal of Signal Processing.
- May 2021: Participation in a Panel at the University of Ioannina, Greece. [video]
- Sep 2020: Invited Talk on Content-gnostic Bitrate Ladder Prediction for Adaptive Video Streaming, Förderverein Technische Fakultät, Alpen-Adria-Klagenfurt University, Austria. [slides and video]
- Jan- 2020: Technical Program Co-chair of PCS 2021.
Projects
- 2021-2022 5G Edge XR: Coding for Volumetric Content Delivery
- 2021-2022 AI in Video Production Workflows, Bristol+Bath Creative Cluster, UKRI
- 2021-2022 Sustainable Video Communications, Bristol+Bath Creative Cluster, UKRI
- 2018-2021 Leverhulme Early-Career Fellowship: Deep Video Analysis and Compression
- 2017-2018 EPSRC Platform Grant: Video Texture Analysis
- 2015-2017 FP7 MSCA ITN: ProVision - Perceptual Video Compression
Research Outputs
- Study of Compression Statistics and Prediction of Rate-Distortion Curves for Video Texture [paper]
A. Katsenou, M. Afonso, and D. R. Bull, Signal Processing: Image Communication, vol. 101, 2022.
- Efficient Bitrate Ladder Construction for Content-Optimised Adaptive Video Streaming [paper] [dataset]
A. V. Katsenou, J. Sole, and D. R. Bull, IEEE Open Journal of Signal Processing, vol.2, 2021.
- BVI-SynTex: A Synthetic Video Texture Dataset for Video Compression and Video Quality Assessment [paper] [dataset]
A. Katsenou, G. Dimitrov, D. Ma, and D. R. Bull, IEEE Transactions on Multimedia, vol.23, 2021.
- Feature Selection is Critical for 2-Year Prognosis in Advanced Stage High Grade Serous Ovarian Cancer by Using Machine Learning [paper]
A. Laios, A. Katsenou, Y. Sheng Tan, R. Johnson, M. Otify, A. Kaufmann, S. Munot, A. Thangavelu, R. Hutson, T. Broadhead, G. Theophilou, D. Nugent, and D. De Jong Cancer Control, vol.28, Jan. 2021.
- VMAF-based Bitrate Ladder Estimation for Adaptive Streaming [paper]
A. V. Katsenou, F. Zhang, K. Swanson, M. Afonso, J. Sole and D. R. Bull, Picture Coding Symposium, Bristol, UK, 2021.
- Enhancing VMAF through New Feature Integration and Model Combination [paper]
F. Zhang, A. V. Katsenou, C. Bampis, L. Krasula, Z. Li, and D. R. Bull, Picture Coding Symposium, Bristol, UK, 2021.
- Feature selection for two-year prognosis in advanced stage high grade serous ovarian cancer using machine learning methods [paper]
A. Laios, A. V. Katsenou, Y. Tan, M. Otify, R. Hutson, A. Kaufmann A, S. Munot, A. Thangavelu, D. De Jong, T. Broadhead, G. Theophilou, D. Nugent, International Journal of Gynecologic Cancer, 2021.
For all papers and datasets see the links below: