Stereoscopic Test Patterns for Depth Algorithm Performance Testing
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Solution Overview
Problem
Existing stereoscopic imaging systems lack comprehensive testing methods to evaluate the performance of stereoscopic algorithms independently of the physical imaging system, leading to imprecision and reduced effectiveness in tasks requiring accurate depth perception.
Innovation Solution
Utilize a stereoscopic test pattern to generate synthetic stereoscopic images, allowing for the independent testing of stereoscopic algorithms by analyzing features of decreasing size and separation, and apply these patterns to both synthetic and physical systems to determine resolution and sharpness limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional imaging quality metrics are used for stereoscopic imaging, then general imaging quality can be assessed, but stereoscopic-specific performance metrics such as depth accuracy and algorithm performance cannot be properly evaluated
Solution Approach 1:
The patent creates synthetic stereoscopic test images that replicate real-world stereo pairs with known ground truth depth values. These synthetic copies allow algorithm performance to be measured precisely without the variability of physical test objects, enabling accurate depth measurement precision while maintaining adaptability through software-based test generation.
Solution Approach 2:
The patent systematically varies parameters in synthetic test images including disparity ranges, feature sizes, and noise levels to create comprehensive test suites. This allows the testing methodology to adapt to different stereoscopic algorithms and operating conditions while maintaining precise measurement capabilities through controlled parameter adjustments.
2Reliability
If physical test objects are used for stereoscopic system calibration, then system-level performance can be measured, but algorithm performance cannot be tested independently of hardware limitations
Solution Approach 1:
The patent separates the testing of stereoscopic algorithms from physical imaging systems by using synthetic test images. This segmentation allows algorithm performance to be evaluated independently without the confounding factors of hardware limitations, while physical systems can still be calibrated using the same synthetic tests combined with actual camera captures.
Solution Approach 2:
The patent introduces synthetic test images as an intermediary between algorithm developers and physical testing systems. These synthetic images serve as a common test bed that can be used to evaluate algorithms independently and then transfer the testing framework to physical systems, reducing overall system complexity by providing a unified testing approach.
3Productivity
If stereoscopic algorithms are tested without independent testing methods, then development can proceed quickly, but performance imprecision and reduced effectiveness occur in applications requiring accurate depth information
Solution Approach 1:
The patent implements preliminary testing using synthetic stereoscopic images during the algorithm development phase. By performing depth precision measurements on synthetic data with known ground truth before deploying to physical systems, developers can quickly iterate and refine algorithms while ensuring measurement precision is achieved, thus maintaining both productivity and accuracy.
Data Source
AI summary
Approaches presented herein provide for the testing of imaging algorithms and systems. In at least one embodiment, a stereoscopic test pattern can be obtained that includes a number of features that vary in width and separation, such as may comprise a set of radial elements that converge toward a center point. A stereoscopic image of an instance of the pattern can be analyzed, such as at a set of radial positions, to make various measurements, including a limit on the ability to distinguish between different features. A pair of synthetic images of the pattern can be generated in order to test aspects of a stereoscopic algorithm used to generate stereoscopic images, with such testing being separate from the physical system, and a physical object can be generated that includes a representation of the pattern in order to be able to test the physical stereoscopic imaging system.