研究目的
To discuss key techniques of the single view point (SVP) catadioptric-omnidirectional vision system, including system composition, optical imaging principle, unified-sphere imaging model, and image unwrapping methods, with a focus on comparing different projection models for panoramic image expansion.
研究成果
The spherical uniform imaging model accurately represents the SVP panoramic vision system imaging process, offering advantages such as clear imaging process, fewer parameters, and simpler calculations. Experimental results show that the cylindrical expansion algorithm based on this model is faster and more suitable for real-time tasks compared to methods using the optical path imaging model.
研究不足
The imaging system may not be perfectly rotationally symmetric if focal lengths of horizontal and vertical axes are not equal, which can affect expansion accuracy for tasks like 3D positioning. The perspective expansion method has higher computational complexity due to additional trigonometric calculations.
1：Experimental Design and Method Selection:
The study involves analyzing and deducing the unified-sphere imaging model for SVP panoramic vision systems, and comparing image unwrapping methods based on different projection models (cylindrical and perspective expansion).
2：Sample Selection and Data Sources:
Panoramic images were acquired using a single viewpoint panoramic camera.
3：List of Experimental Equipment and Materials:
A computer with dual-core Pentium G2020 CPU, 2.9GHz, 4GB memory, Windows7 operating system, and Visual C++ editor software. A single viewpoint panoramic camera was used for image acquisition.
4：9GHz, 4GB memory, Windows7 operating system, and Visual C++ editor software. A single viewpoint panoramic camera was used for image acquisition.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Acquire a panoramic image with the camera. Use optical path imaging model and spherical uniform imaging model to calculate average time for image expansion (500 times for each image). Compare computation times for different resolutions of cylindrical and perspective images.
5：Data Analysis Methods:
Compare computation times between models and resolutions, analyze reasons for differences in time (e.g., use of look-up table method for cylindrical expansion vs. point-by-point calculation for perspective expansion).
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