Multi-Camera Calibration via Environmental Event Detection
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Solution Overview
Problem
Current multiple viewpoint image capturing systems for three-dimensional space reconstruction face challenges in maintaining accuracy and availability due to changes in camera positions or attitudes, leading to deterioration in free-viewpoint video generation and scene analysis performance.
Innovation Solution
A system comprising multiple cameras with a circumstance sensing unit and an event detector that senses environmental changes and determines when to perform camera calibration, ensuring accurate reflection of camera parameters in real-time, thereby stabilizing three-dimensional space reconstruction and recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera calibration is performed frequently to maintain accuracy, then measurement precision is improved, but loss of time increases due to repeated calibration interruptions
Solution Approach 1:
The system transitions from static periodic calibration to dynamic event-triggered calibration. The calibration process is activated dynamically based on detected events (vibrations, temperature changes, humidity changes) rather than following a fixed schedule, allowing the system to balance accuracy maintenance with operational continuity.
Solution Approach 2:
The system implements feedback through sensors that continuously monitor environmental conditions and camera states. When sensors detect events indicating potential calibration degradation, the system responds by triggering calibration, creating a closed-loop control mechanism that maintains accuracy only when necessary.
2Reliability
If camera calibration is performed continuously to maintain stability, then reliability is improved, but productivity decreases due to constant calibration operations
Solution Approach 1:
The system uses periodic sensing to detect events that trigger calibration, rather than performing continuous calibration. Sensors monitor conditions periodically and initiate calibration only when specific event thresholds are met, creating a rhythm of operation that maintains reliability without constant intervention.
Solution Approach 2:
The system performs self-diagnosis through sensor monitoring and automatically triggers calibration when needed, without requiring external intervention or continuous operational pauses. The multi-camera system self-regulates its calibration needs based on environmental feedback.
3Measurement precision
If multiple sensors are deployed to detect calibration events accurately, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system combines multiple sensor types (vibration, temperature, humidity) into an integrated event detection framework. Rather than treating each sensor independently, the system merges their inputs to comprehensively detect calibration events, achieving high detection accuracy through sensor fusion while managing complexity through unified processing.
Data Source
Figure 1(a)~1(e)
Figure 2
Figure 3
AI summary
A multiple viewpoint image capturing system (1000) includes: a plurality of cameras (100) that capture videos in a predetermined space from different positions; a circumstance sensing unit (160) that senses at least one of circumstances of the respective cameras (100) and circumstances of the predetermined space, and outputs the sensed circumstances in a form of capturing circumstance information; and an event detector (202a) that detects a predetermined event based on the capturing circumstance information, determines whether to perform camera calibration in a case of detecting the predetermined event, and outputs camera calibration information that indicates the camera calibration to be performed in a case of determining that the camera calibration is to be performed.