Prediction of encoding bitrate for each CRF value using video features and deep learning
| Title | Prediction of encoding bitrate for each CRF value using video features and deep learning |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Choi, Hankaram, Bae, Yongchul |
| Conference Name | 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) |
| Keywords | Bit rate, Bitrate, CRF, Deep Learning, deep video, encoding, Error analysis, Metrics, Predictive models, pubcrawl, resilience, Resiliency, Scalability, Time series analysis, Video compression |
| Abstract | In this paper, we quantify elements representing video features and we propose the bitrate prediction of compressed encoding video using deep learning. Particularly, to overcome disadvantage that we cannot predict bitrate of compression video by using Constant Rate Factor (CRF), we use deep learning. We can find element of video feature with relationship of bitrate when we compress the video, and we can confirm its possibility to find relationship through various deep learning techniques. |
| DOI | 10.1109/SCISISIS55246.2022.10001859 |
| Citation Key | choi_prediction_2022 |