Smart Glasses Object Location via Pre-captured Image Correlation

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Solution Overview

Problem

Individuals spend significant time and resources searching for lost objects due to inadequate methods for object location assistance.

Innovation Solution

Smart glasses equipped with imagers and processors that utilize computer vision and AI/ML to capture, analyze, and correlate images, enabling users to locate misplaced items by displaying relevant images and locations based on timestamps and environmental similarities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If manual searching methods are used to find lost objects, then no additional technology is required, but significant time and resources are wasted

Engineering Contradiction:

Improvetime spent searching for lost objectsVSAvoidcomplexity of object location system

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by continuously capturing images with imagers and preprocessing them to identify objects and their locations before they are needed. When a user queries for a lost object, the system can quickly retrieve relevant information from pre-processed data, significantly reducing search time without requiring complex real-time processing

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates visual copies of objects through captured images and displays them on the head-mounted display. By presenting image copies rather than requiring physical inspection of numerous objects, the system dramatically reduces the time needed to locate lost items while keeping the overall system complexity manageable

Inventive Principle:

Principle #26Copying

2Measurement precision

If comprehensive image analysis is performed to identify lost objects, then object location accuracy is improved, but processing time and computational resources increase

Engineering Contradiction:

Improveaccuracy of object location identificationVSAvoidprocessing time for image analysis

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system applies partial action by selectively analyzing only those images that contain potential matches for the queried object, rather than performing exhaustive analysis on all captured images. The correlation techniques filter the dataset to focus computation on relevant time periods and locations, achieving high accuracy without the time cost of complete analysis

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent replaces manual mechanical searching with automated computational methods. Image recognition algorithms and correlation techniques automatically identify objects and their locations, substituting human visual inspection and physical searching with efficient computational processes that provide both high accuracy and rapid results

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If multiple images are displayed to help identify lost objects, then identification accuracy is improved, but information overload may occur

Engineering Contradiction:

Improveaccuracy of object identificationVSAvoidease of using the system

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system applies local quality by displaying images with differentiated visual characteristics based on their relevance to the query. Images are presented with varying prominence, timing, or visual markers that highlight their relationship to the lost object, allowing users to quickly identify relevant information without being overwhelmed by uniform presentation of all images

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11176375B2Smart glasses lost object assistance

Publication Date: 2021.11.16 SONY GROUP CORP

AI summary

An assembly includes a head mount such as smart glasses wearable on a head of a user. An imager is on the head mount and is configured to generate images of objects. A processor accesses the images responsive to a query and presents images of objects on a display of the head mount to assist the user in identifying, for example, where a lost object was last seen.