View Image Quality Evaluation Using Predefined Measurements
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Solution Overview
Problem
The evaluation of view images, which map viewpoints from scene shots to a reference, is laborious and prone to errors due to manual or automated processes, leading to unreliable results, necessitating increased data collection efforts to achieve reliable outcomes.
Innovation Solution
A method and device that evaluate view images using predefined quality measurements to objectively assess their reliability, allowing for the selection of high-quality images and reducing the need for additional data collection by categorizing images into quality classes based on their accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation of view images is performed, then evaluation accuracy can be maintained, but time consumption and labor costs increase significantly
Solution Approach 1:
The system performs self-evaluation by automatically assessing view image quality using predefined quality measurements. The evaluation unit computes quality values without human intervention, allowing the system to serve itself in the evaluation process, thus reducing labor costs and time consumption while maintaining consistent evaluation standards.
Solution Approach 2:
The patent replaces the manual mechanical evaluation process with an automated computational system. The evaluation unit uses algorithms to compute quality values based on predefined measurements, substituting human manual assessment with automated image processing and analysis techniques.
2Productivity
If automated algorithms are used to create view images, then processing speed increases, but errors in referencing and object recognition occur
Solution Approach 1:
The system implements feedback mechanisms where quality measurements are continuously computed and used to assess the reliability of automated view image creation. The evaluation unit provides feedback on quality values, allowing the system to identify and correct errors in referencing and object recognition, thereby improving reliability while maintaining automated processing speed.
Solution Approach 2:
The patent applies preliminary quality measurements and predefined evaluation criteria before final view image generation. By establishing quality thresholds and measurement standards in advance, the system can pre-filter and validate automated processing results, reducing errors in referencing and object recognition before they propagate through the evaluation process.
3Reliability
If multiple quality measurements are applied, then evaluation comprehensiveness improves, but computational complexity increases
Solution Approach 1:
The evaluation system segments the quality assessment into multiple independent quality measurements, each evaluating specific aspects of view image quality. This segmentation allows the system to apply comprehensive multi-faceted evaluation while managing computational complexity by dividing the overall assessment into separate, modular measurement components that can be processed independently.
Solution Approach 2:
The patent employs parameter changes by adjusting quality measurement thresholds and weights based on evaluation needs. By dynamically modifying measurement parameters rather than fixing them, the system achieves comprehensive evaluation adaptability while optimizing computational resources, reducing overall computational complexity through intelligent parameter management.
Data Source
AI summary
The invention relates to a method for evaluating at least one view image (M) in order to image at least one viewpoint, which is provided in relation to at least one scene shot (S) of a scene (12), and/or at least one view direction of at least one person (10), said view direction being provided in relation to the at least one scene shot (S), towards a reference, the content of which matches at least one part of the scene (12). The at least one scene shot (S) is provided with the at least one assigned viewpoint (B) and/or the at least one assigned view direction, and the reference (R) is provided together with a result (B′) of the at least one view image (M). Furthermore, the at least one view image (M) is evaluated by means of at least one predefined quality measurement (GM), and the result of the evaluation is provided.