Stereo-aware panorama conversion using ray tracing
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Solution Overview
Problem
Combining panoramic images with different projections introduces visual distortions due to mismatches in optics, particularly when stereoscopic panoramas are created with mismatched camera rigs or computer-generated projections, leading to viewer discomfort and visual discontinuities.
Innovation Solution
The technique involves mapping pixels from one panoramic image to another using ray tracing, accounting for arbitrary projections and stereo camera rig configurations through metadata, which offsets the origin of rays to compensate for interpupillary distance and rotation, ensuring minimal visual distortions by aligning UV coordinates and Euler angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If panoramic images are projected onto a planar surface, then the viewing area is enlarged, but visual distortions are introduced due to projection mismatch
Solution Approach 1:
The patent transitions from 2D planar projection to 3D spherical projection, mapping panoramic images onto a sphere rather than a flat surface. This dimensional change allows the image to wrap around the viewer, eliminating projection distortions while maintaining a large viewing area. The spherical coordinate system enables accurate representation of omnidirectional views without the warping that occurs in planar projections.
Solution Approach 2:
The patent introduces an intermediary transformation process that converts between different projection coordinate systems (e.g., equirectangular, stereographic, fisheye) through a common spherical reference frame. This intermediary spherical coordinate system acts as a mediator that reconciles different projection methods, allowing accurate alignment and combination of panoramic images captured with different camera rigs or projection preferences.
2Adaptability or versatility
If stereoscopic panoramas are created with mismatched camera rigs, then the immersive effect is enhanced, but visual discontinuities and distortions are introduced
Solution Approach 1:
The patent systematically adjusts multiple projection parameters including field of view angles, distortion coefficients, and camera calibration data to account for mismatches between left and right camera rigs. By changing these parameters dynamically during the stitching process, the system can compensate for differences in camera positioning, focal lengths, and optical characteristics, maintaining visual consistency while preserving the immersive stereoscopic effect.
Solution Approach 2:
The patent implements an iterative optimization process that uses feedback from feature matching and seam detection to continuously adjust projection parameters and alignment transformations. By monitoring visual discontinuities at image seams and adjusting the projection model accordingly, the system achieves reliable visual consistency across mismatched camera rigs while maintaining the desired immersive experience.
3Manufacturing precision
If complex projection transformations are applied, then projection mismatches are corrected, but processing complexity increases
Solution Approach 1:
The patent divides the complex projection transformation into separate modular operations: (1) converting input images to a common spherical coordinate system, (2) applying camera calibration and intrinsics transformations, (3) performing feature matching and seam detection, and (4) generating the final stitched panorama. This segmentation allows each operation to be optimized independently and simplifies the overall processing pipeline while maintaining high projection alignment precision.
Solution Approach 2:
The patent performs preliminary actions by pre-computing camera calibration data, intrinsic parameters, and projection matrices before the main stitching process. By preparing these transformation parameters in advance from metadata and calibration images, the system reduces the computational burden during the actual panorama stitching, lowering processing complexity while ensuring accurate projection alignment.
Data Source
AI summary
Techniques are disclosed for conversion of panoramas between different panoramic projections, including stereoscopic panoramic projections. The pixels of one panoramic image are mapped to the pixels of another panoramic image using ray tracing so that the images can be combined without introducing visual distortions caused by mismatches in the optics of each image. The conversion is performed using a process for mapping one or more pixels of an output image to pixels of an input image by tracing a ray between the UV coordinates corresponding to each pixel in the images. The conversion process accounts for arbitrary projections and for arbitrary stereo camera rig configurations by using metadata that describe the projection and positioning of each image being combined. The origin of each ray is offset to account for the interpupillary distance between left and right images and to account for any rotation of the scene.