Object Identification Error Margin Area Calculation
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Solution Overview
Problem
Existing electronic devices that determine objects by pointing face challenges in accurately identifying the intended object due to inaccuracies in position and direction estimation, leading to user dissatisfaction if the intended object is not found.
Innovation Solution
A method that estimates the position and direction of an electronic device using a positioning mechanism and magnetic sensor, calculates intersecting imaginary lines based on error margins, and determines a Point-Of-Interest (POI) within a defined area to enhance the chances of correctly identifying the object, incorporating error handling and statistical models for direction estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If position and direction estimation is performed using standard positioning mechanisms and magnetic sensors, then the device can identify objects by pointing, but measurement errors cause the intended object to not be found
Solution Approach 1:
The patent applies beforehand cushioning by pre-calculating error margins for position and direction measurements before performing object identification. The system determines a first error margin for position estimation and a second error margin for direction estimation, then uses these margins to define an expanded search area and set of candidate POIs. This compensates for measurement errors in advance, ensuring that the intended object is included among candidates even when measurements are imperfect.
Solution Approach 2:
The patent transitions from point-based identification to area-based identification by introducing error margins as additional dimensional parameters. Instead of checking if a single estimated position and direction exactly matches a POI, the system creates a two-dimensional error margin space around the estimation, expanding the search from a point to an area, thereby increasing the probability of capturing the intended object despite measurement inaccuracies.
2Measurement precision
If error margins are incorporated to improve object identification, then more POIs are considered as candidates, but the complexity of determining the correct object increases
Solution Approach 1:
The patent applies segmentation by dividing the error analysis into distinct components: position error margin determination, direction error margin determination, area calculation based on these margins, and candidate POI filtering. Each component is handled separately through dedicated calculation steps, making the overall complex process manageable and systematic rather than attempting to solve all errors simultaneously.
Solution Approach 2:
The patent replaces complex geometric intersection calculations with simplified area-based reasoning. Instead of calculating precise intersections of error ellipses and direction cones, the system substitutes these mechanical geometric operations with area calculations using error margins, determining whether POIs fall within the defined error area, thereby simplifying the computational mechanics while maintaining accuracy.
3Reliability
If multiple candidate POIs are generated due to error margins, then the chance of finding the intended object increases, but user confusion may increase when multiple POIs are presented
Solution Approach 1:
The patent applies feedback by using the calculated error margins to dynamically adjust the presentation of candidate POIs to the user. The system provides feedback about the reliability of each candidate based on how well it fits within the error margins, and uses this feedback to prioritize or filter candidates presented to the user. This feedback mechanism helps reduce user confusion by highlighting the most likely intended object while still maintaining high reliability through comprehensive candidate consideration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the accuracy of object identification by considering error margins, reducing user complexity and ensuring that relevant information about the object is accessible, even in cases where multiple POIs are present, thereby enhancing user experience.
Implementation Method 1
estimating a direction when orienting the electronic apparatus towards the object by a magnetic sensor of the electronic apparatus
Data Source
Figure 1~11
Figure 2
Figure 3~6
AI summary
A method of determining an object in sight with an electronic apparatus, where the object being associated with a Point-Of-Interest, POI, item in a database is disclosed. The method comprises estimating (100) a position of the electronic apparatus by a positioning mechanism; estimating (102) magnitude of error of estimated position; estimating (104) a direction when orienting the electronic apparatus towards the object by a magnetic sensor of the electronic apparatus; estimating (106) magnitude of error of estimated direction; calculating two intersecting imaginary lines in a model of the environment of the electronic apparatus, wherein the two imaginary lines intersect a line of the estimated direction at a side of the electronic apparatus distal to said object, and where a mutual angle between the two imaginary lines and the line of the estimated direction is based on the estimated magnitude of error of estimated direction, and the position where the imaginary lines intersect is determined from the estimated position and the magnitude of error of estimated position, such that an area between the two imaginary lines is formed (108) based on a determined maximum distance of sight; and determining (110) a POI associated with a position within said area such that information about the object associated with the determined POI is obtainable. A computer program and an electronic apparatus are also disclosed.