Invention Grant
- Patent Title: Video encoding optimization for machine learning content categorization
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Application No.: US17488944Application Date: 2021-09-29
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Publication No.: US11902532B2Publication Date: 2024-02-13
- Inventor: Sunil Gopal Koteyar , Mingkai Shao
- Applicant: ATI Technologies ULC
- Applicant Address: CA Markham
- Assignee: ATI Technologies ULC
- Current Assignee: ATI Technologies ULC
- Current Assignee Address: CA Markham
- Agency: Kowert, Hood, Munyon, Rankin & Goetzel, P.C.
- Agent Rory D. Rankin
- Main IPC: H04N19/139
- IPC: H04N19/139 ; H04N19/126 ; G06N20/00 ; G06T3/40 ; H04N19/55 ; H04N19/142 ; G06V20/40

Abstract:
Systems, apparatuses, and methods for performing machine learning content categorization leveraging video encoding pre-processing are disclosed. A system includes at least a motion vector unit and a machine learning (ML) engine. The motion vector unit pre-processes a frame to determine if there is temporal locality with previous frames. If the objects of the scene have not changed by a threshold amount, then the ML engine does not process the frame, saving computational resources that would typically be used. Otherwise, if there is a change of scene or other significant changes, then the ML engine is activated to process the frame. The ML engine can then generate a QP map and/or perform content categorization analysis on this frame and a subset of the other frames of the video sequence.
Public/Granted literature
- US20230095541A1 VIDEO ENCODING OPTIMIZATION FOR MACHINE LEARNING CONTENT CATEGORIZATION Public/Granted day:2023-03-30
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