Panoramic Camera Systems Depth Map Refinement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Capturing and rendering panoramic views from a set of cameras is challenging due to physical limitations, variations in camera positioning and orientation, and difficulties in generating consistent depth maps across overlapping views, leading to artifacts and unrealistic simulations.
Innovation Solution
An optimized arrangement of cameras is determined to maximize field of view coverage, with camera positions and orientations adjusted to minimize energy and ensure optimal coverage, and a computational pipeline is used to generate and refine depth maps using image transforms and filters, ensuring accurate and efficient rendering of panoramic views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If cameras are positioned and oriented to maximize field of view coverage, then the coverage of the environment is improved, but the manufacturing and installation variations cause actual positioning and orientation to differ from the design
Solution Approach 1:
The patent performs calibration before the actual image capture to determine accurate camera positions and orientations. This preliminary calibration step accounts for manufacturing and installation variations by measuring actual camera locations and orientations, then using this information to correct subsequent processing operations.
Solution Approach 2:
The patent implements a feedback mechanism where captured calibration images are processed to determine actual camera parameters, which then feed back into the rendering pipeline. The system continuously refines camera position and orientation information based on actual measurements rather than relying solely on predetermined values.
2Measurement precision
If depth maps are generated using extensive computational resources, then depth estimation accuracy is improved, but processing time and computational cost increase
Solution Approach 1:
The patent applies different processing quality levels to different regions of the image based on depth uncertainty. Areas with higher uncertainty receive more intensive processing and sampling, while regions with lower uncertainty are processed more lightly, optimizing the balance between accuracy and computational efficiency.
Solution Approach 2:
The patent uses partial action by applying random sampling and selective processing only to regions where depth information is most needed or most uncertain, rather than uniformly processing the entire image. This approach reduces overall computational load while maintaining sufficient accuracy in critical areas.
3Area of stationary object
If multiple cameras are used to capture overlapping views, then coverage is improved, but artifacts and inconsistencies are introduced in overlapping regions
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor and adjust the rendering of overlapping regions. Discrepancies between multiple camera views are detected and fed back into the processing pipeline, where they are used to refine depth maps and adjust rendering parameters to eliminate artifacts and inconsistencies.
Solution Approach 2:
The patent applies dynamic adjustment of processing parameters based on the specific characteristics of overlapping regions. The system adaptively modifies depth estimation, blending, and rendering parameters for each overlapping region based on the individual camera characteristics and the specific content being captured.
4Area of stationary object
If camera positions are optimized to maximize field of view, then coverage is improved, but the complexity of determining optimal positions and orientations increases
Solution Approach 1:
The patent performs camera calibration as a preliminary action that simplifies subsequent positioning optimization. By first determining accurate camera positions and orientations through calibration measurements, the system establishes a solid foundation that reduces the complexity of optimizing for specific capture scenarios.
Solution Approach 2:
The patent changes parameters such as camera positions, orientations, and lens characteristics based on actual calibration measurements rather than using fixed predetermined values. This flexibility allows the system to optimize for specific capture scenarios while accounting for actual hardware variations, reducing overall complexity.
Data Source
AI summary
A camera system captures images from a set of cameras to generate binocular panoramic views of an environment. The cameras are oriented in the camera system to maximize the minimum number of cameras viewing a set of randomized test points. To calibrate the system, matching features between images are identified and used to estimate three-dimensional points external to the camera system. Calibration parameters are modified to improve the three-dimensional point estimates. When images are captured, a pipeline generates a depth map for each camera using reprojected views from adjacent cameras and an image pyramid that includes individual pixel depth refinement and filtering between levels of the pyramid. The images may be used generate views of the environment from different perspectives (relative to the image capture location) by generating depth surfaces corresponding to the depth maps and blending the depth surfaces.