Omnidirectional Image Viewpoint Shift Compensation
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Solution Overview
Problem
Conventional methods for processing omnidirectional images captured by wide-angle or fisheye lenses fail to accurately account for viewpoint shifts, leading to significant errors in computer vision applications, especially for objects close to the camera, due to the assumption of central projections.
Innovation Solution
An omnidirectional image format is developed that separates and records viewpoint shift information as a separate channel, allowing for accurate representation and processing of images captured with fisheye and wide-angle cameras, which includes calculating the viewpoint shift magnitude and direction for each pixel and storing it as metadata or an additional image channel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If central projection assumption is used for omnidirectional images, then processing simplicity is improved, but measurement precision deteriorates due to viewpoint shift errors
Solution Approach 1:
The image processing is segmented into two independent parts: standard central projection processing for geometric operations, and separate viewpoint shift compensation processing for accuracy-critical tasks. This allows each part to be optimized independently, maintaining processing simplicity while improving measurement precision where needed.
Solution Approach 2:
A viewpoint shift compensation module acts as an intermediary between the central projection assumption and the final image processing results. It calculates and applies correction factors based on the actual lens characteristics, mediating between the simplified model and physical reality to improve accuracy without complicating the overall system.
2Measurement precision
If viewpoint shift compensation is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Viewpoint shift compensation parameters are pre-calculated and stored during camera calibration, rather than computing them in real-time during image processing. This preliminary action reduces the computational complexity of the main processing pipeline while maintaining high measurement precision through the use of pre-determined correction factors.
Solution Approach 2:
The system changes parameters by introducing viewpoint shift compensation coefficients that modify the standard central projection equations. These parameter changes allow the system to account for lens-specific distortions without fundamentally altering the processing architecture, thus improving accuracy with minimal complexity increase.
3Productivity
If conventional central projection is used, then productivity is improved, but reliability deteriorates due to detectable errors in computer vision applications
Solution Approach 1:
The system dynamically adjusts the level of viewpoint shift compensation applied based on the specific application requirements and image content. For applications where speed is critical and accuracy requirements are moderate, standard processing is used. For applications requiring high reliability, the viewpoint shift compensation is activated, providing a dynamic balance between productivity and reliability.
Data Source
AI summary
A method and system of image processing of omnidirectional images with a viewpoint shift.