Video Frame Pose Filtering for Noise-Induced Jitter Stabilization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Video frames in video processing are affected by noise, leading to video distortion and instability during video conferences or video viewing.
Innovation Solution
A method and apparatus that extracts poses of an object in video frames, determines deflection degree values, generates a control signal based on these values, performs backlash filtering to obtain updated deflection values, and applies image processing based on these values to stabilize the video frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video frames are processed directly without filtering, then processing speed is maintained, but video stability deteriorates due to noise-induced jitter
Solution Approach 1:
The patent applies preliminary action by performing backlash filtering on deflection degree values before they are used for image processing. The filtering operation prepares the data in advance by removing noise-induced jitter, ensuring that subsequent processing steps work with stable, filtered values rather than raw noisy data.
Solution Approach 2:
The patent introduces an intermediary element - the backlash filtering mechanism - that mediates between the raw deflection degree values extracted from video frames and the final image processing operations. This intermediary filters out harmful noise while preserving useful signal, resolving the contradiction between maintaining processing simplicity and achieving video stability.
2Reliability
If backlash filtering is applied to deflection degree values, then video stability improves, but processing time increases
Solution Approach 1:
The patent applies parameter changes by modifying the deflection degree values through backlash filtering, which adjusts these parameters to remove noise-induced variations. The filtering process transforms the raw deflection values into stabilized values that maintain temporal consistency, thereby improving video stability without requiring complex reprocessing of the entire video stream.
3Measurement precision
If pose extraction is performed on noisy video frames, then object detection completeness is maintained, but measurement precision deteriorates due to noise
Solution Approach 1:
The patent applies the taking out principle by extracting and isolating the deflection degree values from the noisy video frames for separate filtering processing. Instead of attempting to filter the entire video frame data, the method extracts only the relevant pose-related parameters and applies backlash filtering specifically to these values, improving measurement precision while minimizing additional processing complexity.
Data Source
AI summary
A video frame processing method, performed by a computer device, includes: receiving video frames carrying noise, wherein the video frames include an object; extracting poses of a part of the object; determining deflection degree values of the part based on the poses; generating a control signal based on the deflection degree values; obtaining updated deflection values based on backlash filtering of the control signal; and performing image processing on the video frames based on the updated deflection values.