VIDEO ENCODING OPTIMIZATION FOR MACHINE LEARNING CONTENT CATEGORIZATION

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.