Context-Aware AR Object Location via Visual Feed Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing visual enhancement devices struggle to effectively indicate objects in a user's environment based on context, such as location, time, and biometric information, leading to inefficient navigation and object detection.
Innovation Solution
The use of augmented reality devices equipped with computer vision and wireless networking components that detect user context through machine learning models, activate object detection frameworks, and provide enhanced visual indications, such as highlighting or navigation arrows, to assist users in locating specific objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional visual enhancement devices are used, then the device structure remains simple, but the object detection accuracy and context awareness are insufficient
Solution Approach 1:
The patent combines multiple functions including camera capture, machine learning-based object detection, context awareness (location, time, biometric data), and augmented reality display into a single integrated system. This merging of previously separate components enables context-aware object detection while managing the complexity through unified architecture.
Solution Approach 2:
The visual enhancement device is designed to perform multiple functions: capturing visual data, processing context information from various sources (location, time, biometric data), detecting objects using machine learning models, and providing enhanced visual feedback. This multi-functionality allows a single device to address diverse detection needs without requiring separate specialized devices.
2Productivity
If context-aware object detection is implemented, then the navigation assistance improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing context data (location, time, biometric information) and pre-loading machine learning models for object detection. By preparing these components in advance and using efficient real-time inference, the system minimizes processing delays while maintaining context-aware navigation assistance.
3Adaptability or versatility
If multiple sensors and processing components are added, then the context detection capability improves, but the device complexity and manufacturing difficulty increase
Solution Approach 1:
The device integrates multiple sensor types (camera, location services, biometric sensors) and processing capabilities into a universal platform that can detect various contexts and objects. This multi-functional design allows a single device architecture to handle diverse detection tasks, simplifying manufacturing compared to producing multiple specialized devices.
Data Source
AI summary
Devices, computer-readable media, and methods for providing an enhanced indication of an object that is located via a visual feed in accordance with a user context are disclosed. For instance, in one example, a processing system including at least one processor may detect a user context from a visual feed, locate an object via the visual feed in accordance with the user context, and provide an enhanced indication of the object via an augmented reality display.