Ground Marker Detection via Adaptive Parameter Adjustment
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Solution Overview
Problem
Existing soil volume measurement systems using ground markers struggle with detection accuracy due to environmental constraints, requiring a single mark size and increasing the burden on implementers in inaccessible areas, as they cannot set parameters based on the feature of the mark.
Innovation Solution
An information processing apparatus and method that acquires and analyzes captured images to detect features of ground markers with different mark sizes, allowing for parameter setting based on the size and altitude, improving detection accuracy and reducing installation burdens by using markers with distinct features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single mark size is used on ground markers, then detection parameters can be standardized, but detection accuracy decreases in varied environments and implementer burden increases in inaccessible areas
Solution Approach 1:
The patent applies local quality by assigning different mark sizes to ground markers based on their specific installation environments. Large marks are used in areas with limited accessibility where implementers struggle to install and collect markers, while small marks are used in easily accessible areas. This localized adaptation of mark characteristics optimizes detection accuracy for each specific environment while managing overall system complexity.
Solution Approach 2:
The patent implements parameter changes by varying the mark size parameter across different ground markers. The detection parameter setting unit dynamically adjusts detection parameters based on the identified mark size, enabling the system to adapt to different mark characteristics. This parameter variation allows the system to maintain high detection accuracy across diverse environments without requiring a completely complex system redesign.
2Measurement precision
If ground markers with different mark sizes are used, then detection accuracy improves in various environments, but the burden on implementers increases due to carrying and managing multiple marker types
Solution Approach 1:
The patent applies self-service by enabling the detection parameter setting unit to automatically identify mark sizes and configure appropriate detection parameters without requiring implementer intervention. The system autonomously adapts to different mark characteristics, eliminating the need for implementers to manually adjust parameters or understand the complexities of different marker types, thus reducing their burden while maintaining high detection accuracy.
Solution Approach 2:
The system dynamically changes detection parameters based on the detected mark size, allowing automatic adaptation to different marker types. This parameter transformation occurs automatically within the detection system, relieving implementers of the burden of manually managing multiple marker types while still achieving environment-optimized detection accuracy.
3Measurement precision
If mark size is increased for better detection in inaccessible areas, then detection accuracy improves, but the physical burden on implementers increases
Solution Approach 1:
The patent applies local quality by strategically deploying large marks only in specific inaccessible areas where detection difficulty arises, rather than using large marks universally. In easily accessible areas, smaller marks suffice, reducing the overall weight and burden on implementers. This localized approach to mark size optimization balances detection accuracy requirements with implementer burden reduction.
Data Source
AI summary
To make it possible to set a parameter, which is used for detection of a mark attached to a ground marker, according to the feature of the mark.Provided is an information processing apparatus including: an acquisition unit that acquires a captured image; a detection unit that detects a feature of a target object in the captured image; and a determination unit that determines, on the basis of the feature, a parameter used for an assessment of whether or not the target object is a predetermined object.