Automated Object Coverage Evaluation via Pixel Mapping
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Solution Overview
Problem
Existing methods for capturing three-dimensional objects using two-dimensional image data are inefficient, requiring manual inspection to ensure comprehensive coverage, and lack effective techniques for evaluating the coverage of objects in visual data.
Innovation Solution
The development of techniques that map pixels in a visual representation of an object to a designated standard view, allowing for the identification of captured portions and providing a user interface to indicate coverage, using grid portions with associated coverage estimation values based on distance and angle, and aggregating these mappings to determine the probability and uncertainty of object coverage across multiple viewpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to ensure comprehensive object coverage, then coverage accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent replaces manual inspection with an automated computer-implemented system that uses image processing algorithms to map pixels from captured images to a standard view of the object. The system automatically determines coverage by analyzing pixel mappings and generating coverage indicators, eliminating the need for manual review while maintaining accurate coverage assessment.
Solution Approach 2:
The system performs self-evaluation of coverage by automatically processing the captured images, mapping pixels to the standard view, and generating coverage indicators without external intervention. The computer-implemented system serves itself by autonomously completing the entire coverage evaluation workflow from image input to coverage assessment output.
2Reliability
If multiple images are captured from various viewpoints to ensure complete object coverage, then coverage completeness is improved, but data processing complexity increases
Solution Approach 1:
The patent divides the object into a standard view that serves as a reference framework, and segments the captured images into mappable pixel regions. By overlaying the standard view onto captured images and mapping corresponding pixels, the system systematically processes multiple images without overwhelming complexity, as each image is processed through a standardized mapping procedure.
Solution Approach 2:
The standard view acts as an intermediary between multiple captured images and the final coverage assessment. Instead of directly comparing multiple complex images against each other, the system uses the standard view as a common reference frame to which all captured images are mapped, simplifying the integration and analysis of multi-viewpoint data.
3Productivity
If automated pixel mapping is implemented to evaluate object coverage, then processing efficiency is improved, but measurement precision may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms by generating coverage indicators that provide visual or quantitative feedback about the coverage status. This feedback allows for verification and adjustment of the automated mapping process, ensuring that the efficiency gains from automation do not compromise the accuracy of coverage evaluation. The coverage indicators serve as a feedback loop to validate the mapping results.
Data Source
AI summary
Pixels in a visual representation of an object that includes one or more perspective view images may be mapped to a standard view of the object. Based on the mapping, a portion of the object captured in the visual representation of the object may be identified. A user interface on a display device may indicate the identified object portion.