Light Field Camera Array Self-Calibration for Telepresence
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Solution Overview
Problem
Current video conferencing technologies, including telepresence systems, face challenges in providing immersive and engaging experiences due to inconsistencies in image capture and rendering, particularly in maintaining eye gaze and real-time responsiveness across geographically disparate locations.
Innovation Solution
The implementation of a light field camera system with a controller that captures and processes image data from multiple cameras, detects inconsistencies, and generates correction data to ensure consistent and immersive views, utilizing a light field camera array and a telepresence device controller to synchronize and render images in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a light field camera array is used to capture image data from multiple cameras, then the immersive experience and depth cues are improved, but the complexity of detecting and correcting miscalibration between cameras increases
Solution Approach 1:
The system performs self-calibration by automatically detecting miscalibration between cameras through image data analysis and generating correction data without requiring external calibration equipment or manual intervention. The camera array calibrates itself using the captured image data from multiple cameras, eliminating the need for separate calibration procedures.
Solution Approach 2:
The system implements a feedback mechanism where image data from multiple cameras is continuously analyzed to detect inconsistencies, and correction data is generated and applied back to the camera array. This closed-loop feedback process ensures ongoing calibration maintenance and optimizes the immersive experience dynamically.
2Speed
If real-time image processing and correction is performed, then the responsiveness and eye gaze maintenance are improved, but the computational load and processing time increase
Solution Approach 1:
The system performs preliminary calibration during manufacturing or initial setup, establishing baseline correction data before actual use. This pre-processing reduces the computational burden during real-time operation, as the system only needs to apply pre-computed correction factors rather than performing full calibration calculations continuously.
3Area of stationary object
If multiple cameras are used to capture image data, then the field of view and scene coverage are improved, but the inconsistency between camera views increases
Solution Approach 1:
The system replaces mechanical calibration adjustments with computational correction. Instead of physically adjusting camera positions and orientations to achieve alignment, the system uses image processing algorithms to detect and correct view inconsistencies computationally, maintaining reliability while preserving the benefits of multiple camera perspectives.
Data Source
AI summary
Techniques in connection with a light field camera array are disclosed, involving obtaining a first image data from a first image camera included in the light field camera array for a first time, obtaining a second image data from the first image camera included in the light field camera array for a second time before the first time, obtaining a third image data from a second image camera included in the light field camera array at a different position than the first image camera and having a field of view overlapping a field of view of the first imaging camera, detecting an inconsistency in a view of a scene between the first image data and the second image data and/or the third image data, automatically attempting to generate, in response to the detection of the inconsistency, correction data for the first image camera to reduce or eliminate the detected inconsistency.