Portable Two-Camera Omni-Imaging Device for Indoor Scene Coverage
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Solution Overview
Problem
Conventional street view systems face challenges in capturing images of narrow, indoor, or uneven environments due to the weight and mobility limitations of existing imaging devices, leading to inefficiencies in data processing and coverage.
Innovation Solution
A portable two-camera omni-imaging device captures upper and lower omni-images, which are then processed through image inpainting, dehazing, and pano-mapping to form panoramic images that are stitched using dynamic programming and homographic transformation techniques, reducing the image matching burden and enhancing mobility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If heavy imaging devices (Street View Car, Trike, Snowmobile) are used to capture street scenes, then comprehensive scene coverage is achieved, but mobility and ease of operation deteriorate due to weight (about 150 kg)
Solution Approach 1:
The imaging system is segmented into two separate cameras positioned at different heights (upper and lower), each capturing specific fields of view. This segmentation allows the system to be broken down into manageable components that can be processed independently, reducing the overall complexity and weight while maintaining comprehensive coverage
Solution Approach 2:
The patent introduces a vertical dimension by positioning cameras at different heights (upper and lower), capturing images in both horizontal and vertical directions. This multi-dimensional approach enables comprehensive scene coverage without requiring a single heavy omnidirectional camera, improving mobility while maintaining reliability
2Loss of information
If traditional multi-camera systems with eight digital cameras, one fish-eye camera, and three laser range finders are used, then complete scene data is captured, but device weight increases to about 150 kg
Solution Approach 1:
The patent extracts only the essential imaging components needed for omnidirectional coverage, using just two cameras positioned strategically. This extraction eliminates unnecessary heavy equipment (laser range finders, multiple redundant cameras) while maintaining the ability to capture complete scene data through clever geometric positioning and processing
Solution Approach 2:
The system uses two simplified camera setups (upper and lower) that collectively capture the same comprehensive scene information as more complex systems. By creating simplified copies of the imaging function at different positions, the patent achieves complete scene data with reduced weight
3Reliability
If a large number of images from multiple cameras are stitched together, then complete panoramic coverage is achieved, but processing time increases due to large data amount
Solution Approach 1:
The patent extracts and processes only the essential overlapping regions between upper and lower panoramic images. By focusing computation on these critical overlapping areas rather than processing all image data, the system achieves complete panoramic coverage with significantly reduced processing time
Solution Approach 2:
The stitching process is segmented into distinct stages: capturing upper and lower hemispherical views separately, unwrapping each to form panoramic images, and then stitching only the overlapping regions. This segmentation of the processing pipeline reduces the overall computational burden while maintaining complete panoramic coverage
Data Source
AI summary
A scene imaging method using a portable two-camera omni-imaging device for human-reachable environments is disclosed. Firstly, an upper omni-image and a lower omni-image of at least one scene are captured. Next, image inpainting and image dehazing perform on the upper omni-image and the lower omni-image. Next, image unwrapping performs on the upper omni-image and the lower omni-image by a pano-mapping table, so as to form an upper panoramic image and a lower panoramic image respectively, and the upper panoramic image and the lower panoramic image respectively have an upper part and a lower part overlapping each other. Finally, a data item on the upper part and the lower part is obtained by view points of the scene and the pano-mapping table, thereby stitching the upper and lower panoramic images.