Intel corporation (20240331168). METHODS AND APPARATUS TO DETERMINE CONFIDENCE OF MOTION VECTORS simplified abstract
Contents
METHODS AND APPARATUS TO DETERMINE CONFIDENCE OF MOTION VECTORS
Organization Name
Inventor(s)
James Holland of Folsom CA (US)
Muhammad Hamdan of Palo Alto CA (US)
Timothy Chong of Palo Alto CA (US)
METHODS AND APPARATUS TO DETERMINE CONFIDENCE OF MOTION VECTORS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240331168 titled 'METHODS AND APPARATUS TO DETERMINE CONFIDENCE OF MOTION VECTORS
The patent application describes a system for determining the confidence of motion vectors in video frames.
- The system generates feature data for a motion vector based on pixel data in two video frames.
- It calculates a confidence score for the motion vector using a model and the feature data.
- The system then combines the motion vector and confidence score to estimate the accuracy of the motion vector.
Potential Applications: - Video compression algorithms - Video editing software - Motion tracking in surveillance systems
Problems Solved: - Improving the accuracy of motion vectors in video processing - Enhancing the quality of motion-based applications
Benefits: - Increased efficiency in video processing - Improved accuracy in motion tracking - Enhanced user experience in video editing
Commercial Applications: Title: "Enhanced Motion Vector Confidence System for Video Processing" This technology can be used in video editing software to provide more accurate motion tracking and enhance the overall quality of video content. It can also be integrated into surveillance systems for improved motion detection capabilities.
Questions about the technology: 1. How does the system determine the confidence score for a motion vector? - The system calculates the confidence score based on a model and feature data associated with the motion vector. 2. What are the potential drawbacks of relying on motion vectors in video processing? - Motion vectors may not always accurately represent the motion in a video frame, leading to potential inaccuracies in applications that rely on them.
Original Abstract Submitted
systems, apparatus, articles of manufacture, and methods are disclosed to determine confidence of motion vectors. examples disclosed herein are to generate feature data associated with a motion vector, the motion vector generated based on a first block of pixel data in a first video frame and a second block of pixel data in a second video frame, determine a confidence score for the motion vector based on a model and the feature data, and concatenate the motion vector and the confidence score to output an estimated likelihood that the motion vector is accurate.
