Dynamic optimizer — a perceptual video encoding optimization framework

Video encoding has fueled academic research over the past 25 years and enabled compelling products and services. Many companies are built around video encoding and transmission — Netflix and Google’s YouTube are two prime examples of video-centric companies. The fundamentals of video encoding haven’t changed for all these years, as modern video streams are produced with the same type of encoding parameters that have been used since MPEG-1 [1]: a certain frame resolution is chosen, together with a group-of-pictures (GOP) structure that imposes periodic Intra pictures, and a target bitrate that is (approximately) met by either a single-pass or two-passes over the input video frames.

Source: Dynamic optimizer — a perceptual video encoding optimization framework

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