Video Position Deviation Detection via Differential Subframe Patterns
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Solution Overview
Problem
Existing video processing methods struggle to accurately detect deviations in the position of a displayed video without introducing noise, as the extraction of pattern images from superimposed subframes is hindered by high-frequency components from the original image.
Innovation Solution
A video processing method that superimposes identical first and second pattern images on subframes, captures these subframes, and calculates their difference to extract a third pattern image for deviation detection, while ensuring the subframes on which the patterns are superimposed are identical to minimize noise interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pattern images are superimposed on subframes for deviation detection, then detection capability is improved, but noise from high-frequency components of the original image interferes with pattern extraction
Solution Approach 1:
The frame is divided into multiple subframes, and different pattern images are superimposed on different subframes. By capturing and differentiating between these segmented subframes, the system can extract pattern information while eliminating high-frequency noise from the original image content.
Solution Approach 2:
Instead of trying to filter noise from the captured image, the patent inverts the approach by superimposing distinct pattern images on different subframes and using differentiation to isolate the patterns. The noise is eliminated by computing the difference between captured subframes, which cancels out the high-frequency components of the original image while preserving the pattern information.
2Measurement precision
If multiple subframes are processed to extract pattern images, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The video frame is segmented into multiple subframes, each carrying a distinct pattern image. This segmentation allows the system to process and differentiate between subframes to extract pattern information, achieving accurate deviation detection through a systematic division of the processing task.
Solution Approach 2:
The patent uses identical or complementary pattern images superimposed on different subframes. By capturing multiple copies of subframes with differentiated patterns and processing them through subtraction, the system efficiently extracts pattern information without requiring complex analysis of each individual subframe.
3Measurement precision
If pattern images are superimposed on video content, then deviation detection becomes possible, but user recognition of patterns may occur
Solution Approach 1:
The pattern images are designed with specific local characteristics that are optimized for machine detection rather than human perception. By controlling the spatial frequency, contrast, and distribution of patterns in specific regions of the subframes, the system achieves detectability by capture devices while remaining imperceptible to human users during normal video playback.
Data Source
AI summary
A video processing method comprises outputting a first superimposed subframe obtained by superimposing a first pattern image on a first subframe, and a second superimposed subframe obtained by superimposing a second pattern image on a second subframe for display on a display screen. The video processing method comprises capturing first superimposed subframe and the second superimposed subframe displayed on the display screen. The video processing method comprises acquiring a third pattern image from a difference between the captured first superimposed subframe and the captured second superimposed subframe. The video processing method comprises detecting a deviation in a position where a video projected on the display screen is displayed by comparing a feature point of the acquired third pattern image with a reference feature point. The first subframe and the second subframe are the identical images.