Dynamic Depth Component Adjustment for 6DoF Video
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Solution Overview
Problem
Current 6-DoF VR video shooting systems require a large number of cameras, leading to significant computational resources needed for generating depth data, which can be inefficient and impractical for dynamic scenes.
Innovation Solution
A method is proposed that dynamically adjusts the number of depth components by analyzing the completeness of the first set of depth components, allowing for a reduction in the number of depth components in subsequent sets, thereby optimizing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large number of cameras are used to capture 6-DoF video of dynamic scenes, then depth data completeness is improved, but computational resource requirements increase
Solution Approach 1:
The system dynamically adjusts the number of depth components based on scene analysis. The processor analyzes the first set of depth components to determine completeness, then selectively reduces the number of depth components in subsequent sets when completeness is sufficient, creating a dynamic adaptation to scene requirements rather than using a fixed large number of cameras throughout
Solution Approach 2:
The patent changes the parameter of depth component count based on scene analysis results. When the first set of depth components is determined to be complete, the system reduces the number of depth components in the second set, optimizing computational resources while maintaining depth data quality when sufficient
2Measurement precision
If all cameras continuously capture images for depth generation, then depth data accuracy is maintained, but data transmission volume increases
Solution Approach 1:
The system discards redundant depth components when the scene is determined to be sufficiently captured by existing components. The processor analyzes depth component completeness and selectively reduces the number of depth components in subsequent sets, discarding unnecessary data while preserving essential depth information for accurate rendering
Data Source
AI summary
A method for generating depth data for a six degree of freedom, 6DoF, video of a scene. The method comprises obtaining a first set of images of the scene, generating a first set of depth components based on the first set of images and analyzing the first set of depth components to determine completeness of the depth components. A second set of images of the scene are further obtained and a second set of depth components are generated based on the second set of images, wherein, if the analysis determines the first set of depth components to be overcomplete, the number of depth components in the second set is selected to be smaller than the number of depth components in the first set.