Fast macroblock mode decision for H.264/AVC baseline profile video transcoder based on support vector machines

Machine learning‐based H.264/AVC to HEVC transcoding via motion information reuse and coding mode similarity analysis

“…To develop transcoding algorithms that provide improved efficiency, accuracy, and reliability, machine learning (ML) methods have been implemented to solve prediction and classification problems in transcoding. A fast MB mode decision scheme based on support vector machines is proposed for video transcoder in [10]. In 2014, Peixoto proposed an H.264/AVC to HEVC transcoding algorithm based on ML [11].…”

Memory Copy Optimization for Streaming Gateway Transcoding: Models and Algorithms

“…A streaming media gateway is an interconnect between different types of media networks, undertaking tasks such as protocol translation [1] , traffic shaping [2] , bit rate adaptation [3] or resolution compression [4] . In this paper we focus on the protocol translation function, with which a gateway replaces the transport protocol encapsulation while probably leaving the payload media data probably unchanged [5] .…”

Performance analysis of machine learning for arbitrary downsizing of pre-encoded HEVC video

“…In the existing literature, most machine learning techniques for transcoding are based on offline training [8]- [12]. This means that the prediction model is trained on a set of videos (the training set) and evaluated on a separate test set.…”

“…Alternative fast transcoding techniques predict encoding information by using machine learning to exploit the correlation between the coding information of the input and output video [8]- [13]. Different machine learning algorithms have been used in these transcoding techniques.…”

“…Different machine learning algorithms have been used in these transcoding techniques. Support vector machines (SVM [14]) have been applied for transcoding H.264/AVC bitstreams [8]. Decision trees (DT [15]) are also widely used for transcoding [9]- [12].…”