Fast Multi-rate Encoding for Adaptive Streaming using Machine Learning
US Patent
[PDF]
Hadi Amirpour (Alpen-Adria-Universität Klagenfurt, Austria), Ekrem Çetinkaya (Alpen-Adria-Universität Klagenfurt, Austria), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria)
Abstract: According to embodiments of the disclosure, fast multi-rate encoding may be performed using machine learning by encoding a lowest quality representation to determine encoding parameters, processing raw data of the video using a neural network to obtain an intermediate output comprising encoding features, augmenting the intermediate output with additional encoding features to form a final tensor, and processing the final tensor with another neural network to obtain a classification output comprising a split or not split decision for an image data block. The classification output may be used to encode a highest quality representation, and then other representations of the video.
