Invention Grant
- Patent Title: Systems and methods for rate control in video coding using joint machine learning and game theory
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Application No.: US15352222Application Date: 2016-11-15
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Publication No.: US10542262B2Publication Date: 2020-01-21
- Inventor: Wei Gao , Tak Wu Sam Kwong
- Applicant: City University of Hong Kong
- Applicant Address: HK Kowloon
- Assignee: City University of Hong Kong
- Current Assignee: City University of Hong Kong
- Current Assignee Address: HK Kowloon
- Agency: Norton Rose Fulbright US LLP
- Main IPC: H04N19/147
- IPC: H04N19/147 ; H04N19/124 ; H04N19/172 ; H04N19/159 ; H04N19/176

Abstract:
Systems and methods which provide a joint machine learning and game theory modeling (MLGT) framework for video coding rate control (RC) are described. A machine learning based R-D model classification scheme may be provided to facilitate improved R-D model prediction accuracy and a mixed R-D model based game theory approach may be implemented to facilitate improved RC performance. For example, embodiments may provide inter frame Coding Tree Units (CTUs) level bit allocation and RC optimization in HEVC. Embodiments provide for the CTUs being classified into a plurality of categories, such as by using a support vector machine (SVM) based multi-classification scheme. An iterative solution search method may be implemented for the mixed R-D models based bit allocation method. Embodiments may additionally or alternatively refine the intra frame QP determination and the adaptive bit ratios among frames to facilitate improving the coding quality smoothness.
Public/Granted literature
- US20180139450A1 SYSTEMS AND METHODS FOR RATE CONTROL IN VIDEO CODING USING JOINT MACHINE LEARNING AND GAME THEORY Public/Granted day:2018-05-17
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