Temporal-Spatial Object Filtering for Noisy Measurement Data
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Solution Overview
Problem
Existing measurement technologies struggle to extract required data in environments prone to noise due to measurement errors and unintended objects, making it difficult to select an analysis target effectively.
Innovation Solution
A measurement apparatus that utilizes temporal-spatial constraints to determine whether an object is an analysis target by calculating temporal and spatial matching ratios, using a processor to extract and analyze data from measurement points, and determine if they meet predefined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If measurement data is collected in everyday life environments, then the quantity of measurement data increases, but noise due to unintended objects and measurement errors increases
Solution Approach 1:
The patent segments the measurement data by extracting positions of multiple objects at each time point and grouping them into different groups based on temporal-spatial constraints. This segmentation allows the system to process and filter data from multiple objects separately, enabling effective noise reduction while preserving valid measurement data from intended targets.
Solution Approach 2:
The patent extracts the position information of specific objects from the overall measurement data by calculating distances between object positions and reference positions. This extraction process isolates relevant data from unintended objects, allowing the system to identify and remove noise while retaining useful measurement data.
2Measurement precision
If temporal-spatial constraints are applied to filter measurement data, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining temporal-spatial constraints (time range and space range) before processing measurement data. The system calculates temporal matching ratios and spatial matching ratios based on these predetermined constraints, which simplifies the filtering process and improves measurement precision without requiring complex real-time decision-making algorithms.
Solution Approach 2:
The patent utilizes parameter changes by transforming raw measurement data into standardized metrics (temporal matching ratio and spatial matching ratio) that can be directly compared against threshold values. This parameter transformation simplifies the complexity of evaluating whether objects satisfy temporal-spatial constraints, making the system more manageable while maintaining high measurement precision.
3Quantity of substance
If multiple objects are detected in measurement data, then the quantity of data increases, but difficulty in detecting and measuring the intended target increases
Solution Approach 1:
The patent implements feedback by calculating matching ratios for each detected object against the temporal-spatial constraints and using these ratios to determine whether objects satisfy the constraints. This feedback mechanism allows the system to iteratively evaluate and rank multiple objects, making it easier to identify the intended analysis target among numerous detected objects by selecting those with the highest matching ratios.
Data Source
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AI summary
Provided is a measurement apparatus including a processor and a storage unit. The storage unit holds measurement data of each time point which is obtained by a photographing apparatus, and temporal-spatial constraints. The processor extracts a position of an object from the measurement data of each time point, determines whether the object satisfies the temporal-spatial constraints, and determines, based on a result of the determination on whether the object satisfies the temporal-spatial constraints, whether the object is an analysis target.