Stereoscopic Video Rectification with Post-Inserted Object Preservation
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Solution Overview
Problem
Stereoscopic image processing technologies face challenges in rectifying errors caused by post-inserted objects (PIOs) in stereoscopic images, leading to distorted visibility and inconvenience for users, especially when these objects are inserted after image generation.
Innovation Solution
A method and apparatus for processing stereoscopic video that identifies video segment boundary frames, removes post-inserted objects (PIOs) by determining their type and location, and rectifies the image by aligning elements on the same horizontal line, filling the removed region with surrounding pixel colors, and reinserting the PIO at its original location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If rectification methods (overall conversion or local smoothing transformation) are used to correct stereoscopic image errors, then the alignment between left and right images is improved, but the position and visibility of post-inserted objects (PIOs) become distorted
Solution Approach 1:
The patent segments the stereoscopic image into two distinct parts: the original image content and the post-inserted object (PIO). By detecting the PIO's position and characteristics separately, the system can apply rectification transformations only to the original image while preserving the PIO's intended position and appearance, thus resolving the contradiction between alignment precision and PIO position accuracy.
Solution Approach 2:
The patent performs preliminary detection of the PIO's position, size, and characteristics before applying the rectification transformation. This preliminary action allows the system to compensate for the upcoming transformation by pre-adjusting the PIO's position and parameters, ensuring that the PIO remains undistorted while the original image achieves proper alignment.
2Reliability
If rectification is applied to the entire stereoscopic image including PIOs, then the epipolar alignment is improved, but the PIO visibility and geometric relationship with the original image are distorted
Solution Approach 1:
The patent segments the processing target into the original image and the PIO, applying different processing strategies to each. The original image undergoes full rectification to achieve epipolar alignment, while the PIO is detected, measured, and reinserted separately to maintain its visibility and geometric relationship with the original image.
Solution Approach 2:
The patent applies local quality by treating the PIO differently from the original image. While the original image receives uniform rectification transformation, the PIO area is excluded from this transformation and instead undergoes separate detection, measurement, and reinsertion processes, ensuring that each region receives the appropriate processing quality.
Data Source
AI summary
A method of processing a stereoscopic video includes determining whether a current frame of a stereoscopic video is a video segment boundary frame; determining whether an image error is included in the current frame when the current frame is the video segment boundary frame; and processing the current frame by removing, from the current frame, a post inserted object (PIO) included in the current frame when the image error is included in the current frame.