Multi-Camera Free Viewpoint Capture System Using Zone Segmentation
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Solution Overview
Problem
Current systems for providing immersive experiences with captured video content, such as movies or sports events, often restrict user viewpoint flexibility, leading to discomfort and reduced immersion due to pre-defined or limited viewpoints, and face challenges in capturing sufficient image information and deriving necessary data for free viewpoint navigation.
Innovation Solution
A method and system for capturing and processing content using multiple cameras to generate a three-dimensional representation of the environment, allowing users to freely navigate viewpoints, which includes image fusion techniques to address occlusions and incomplete data, and enables local or remote rendering of free viewpoint experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple cameras are used to capture free viewpoint content, then viewpoint flexibility and immersion are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system divides the capture location into multiple zones, each monitored by specific cameras. This segmentation allows the system to manage complexity by organizing cameras into groups responsible for specific spatial regions, making the multi-camera system more manageable and scalable.
Solution Approach 2:
The system uses a unified data structure and processing framework that handles multiple camera inputs, occlusions, and different viewpoint requirements through a single cohesive architecture. This multi-functional approach reduces overall system complexity by avoiding separate processing pipelines for different scenarios.
2Manufacturing precision
If image fusion techniques are used to address occlusions, then image quality and completeness are improved, but processing time and computational demands increase
Solution Approach 1:
The system performs preliminary organization of camera data into zone-based groups before fusion processing. By pre-structuring the data according to spatial zones and identifying occlusion patterns in advance, the system reduces the computational burden during actual image fusion, thereby decreasing processing time while maintaining quality.
Solution Approach 2:
The system applies image fusion selectively to regions affected by occlusions rather than processing entire images uniformly. This local approach focuses computational resources only on areas needing enhancement, improving image quality where needed while minimizing overall processing time.
3Ease of operation
If free viewpoint navigation is enabled, then user immersion and exploration freedom are improved, but latency and computational demands increase
Solution Approach 1:
The system segments the virtual environment into discrete zones corresponding to physical camera locations. When users navigate between zones, the system efficiently retrieves pre-processed data for the target zone rather than generating all possible viewpoints, significantly reducing latency while maintaining navigation freedom.
Solution Approach 2:
The system creates simplified copies or representations of zone data that can be quickly rendered for different viewpoints. By maintaining pre-processed zone information that can be rapidly copied and adapted to various viewpoint requirements, the system reduces real-time computational demands and latency.
4Loss of information
If more cameras are deployed to capture sufficient image information, then data completeness is improved, but system complexity and cost increase
Solution Approach 1:
The system divides the capture space into zones and assigns specific cameras to monitor specific zones. This segmentation allows the system to achieve complete coverage with fewer cameras by strategically positioning them to monitor designated areas, rather than requiring dense camera deployment throughout the entire space.
Solution Approach 2:
The system introduces zone-based data structures as intermediaries between cameras and the final free viewpoint generation. These zone representations consolidate information from multiple cameras efficiently, reducing the overall system complexity by managing camera data through an organized intermediate layer rather than direct complex integration.
Data Source
AI summary
A method of capturing free viewpoint content at a location includes recording video on each of a plurality of portable video recording devices at the location; each portable video recording device detecting a wireless synchronisation signal transmitted at the location; and each portable video recording device periodically adding a timestamp to its respective recorded video; where the timestamp is responsive to the detected wireless synchronisation signal, thereby enabling synchronisation of a plurality of recorded videos responsive to the timestamps.