Polynomial Curve Correction for Wraparound Video Subject Continuity
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Solution Overview
Problem
Conventional video image editing methods using multi-viewpoint cameras often result in misrecognition or missing information, leading to discontinuity and discomfort when creating wraparound video images, as the position and size of subjects can vary significantly across cameras, causing irregularities in the rotated composite video.
Innovation Solution
A video image editing device that applies labels to images from multiple cameras, extracts and corrects/interpolates position and size information using polynomial approximation curves, adjusts image sizes with an expansion/contraction parameter, and generates a wraparound video image by blending adjacent images of the same size to ensure continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video images are switched along the sequence of cameras arranged to surround the subject, then a wraparound video image is obtained, but position and size irregularities of the subject occur across different camera views
Solution Approach 1:
The patent applies parameter changes by using polynomial expressions to model and correct the position and size parameters of subjects across different camera views. The system generates polynomial expressions based on position information from multiple cameras and uses these to correct irregularities in subject positioning and sizing, thereby maintaining consistency throughout the wraparound video sequence.
2Extent of automation
If skeleton estimation is performed on images from multiple cameras, then subject identification is attempted, but misrecognition or missing information occurs leading to discontinuity
Solution Approach 1:
The patent implements feedback by using polynomial expressions derived from position information of subjects across multiple cameras to correct and refine subject identification. When skeleton estimation fails or produces inconsistent results, the system uses the polynomial models to provide corrective feedback that maintains subject continuity and prevents misrecognition, thereby improving the reliability of automatic subject identification.
3Productivity
If the sizes of subjects in images from different cameras are not uniform, then the wraparound video image shows size variations, but this causes lack of continuity and viewing discomfort
Solution Approach 1:
The patent addresses size consistency by applying parameter changes through polynomial expressions that model subject size across different camera views. The system generates polynomial expressions based on size information from multiple cameras and uses these to correct size variations, ensuring uniform subject appearance throughout the wraparound video while maintaining efficient automated processing.
Data Source
AI summary
A video image editing device or the like, capable of editing a wraparound video image generated by using a plurality of video images captured by multi-viewpoint cameras to be comfortably viewable by viewers, is provided. Based on information about the positions and the sizes of X subjects, a polynomial expression regarding the position of the subject and a polynomial expression regarding the size of the subject are generated. Correction or interpolation of the positions of the H subjects is performed by a polynomial approximation curve using the polynomial expression regarding the position of the subject, correction or interpolation of the sizes of the N subjects is performed by a polynomial approximation curve using the polynomial expression regarding the size of the subject, and the sizes of the N subjects are expanded or contracted with an expansion/contraction parameter p. An intermediate image is generated from two images of the same size corresponding to the photographing devices adjacent to each other, and a wraparound video image is generated, with a parameter indicating the length of the wraparound video image being represented by Tp.