| Read: | Online documentation <https://cd-athena.github.io/VCA/>
| Interact: | Report an issue <https://github.com/cd-athena/VCA/issues/new>
VCA <https://vca.itec.aau.at/>_ is an open source video complexity analyzer. See the online documentation for instructions for building the source.
The primary objective of VCA is to become the best spatial and temporal complexity predictor for every frame/ video segment/ video which aids in predicting encoding parameters for applications like online per-title encoding.
VCA is available as an open source library, published under the GPLv3 license.
Please use "Cite this repository" to extract proper citation options for this repository or use the following:
Vignesh V Menon, Christian Feldmann, Klaus Schoeffmann, Mohammad Ghanbari, and Christian Timmerer. 2023. Green Video Complexity Analysis for Efficient Encoding in Adaptive Video Streaming. In Proceedings of the First International ACM Green Multimedia Systems Workshop (GMSys 2023). Association for Computing Machinery, New York, NY, USA, 259–264. https://doi.org/10.1145/3593908.3593942 <https://doi.org/10.1145/3593908.3593942>_
Vignesh V Menon, Christian Feldmann, Hadi Amirpour, Mohammad Ghanbari, and Christian Timmerer. 2022. VCA: video complexity analyzer. In Proceedings of the 13th ACM Multimedia Systems Conference (MMSys '22). Association for Computing Machinery, New York, NY, USA, 259–264. https://doi.org/10.1145/3524273.3532896 <https://doi.org/10.1145/3524273.3532896>_