AR Object Recognition for Indoor Localization
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Solution Overview
Problem
Current Augmented Reality (AR) systems face challenges in providing immersive and interactive experiences indoors due to limitations in object recognition and localization, as GPS and other localization signals often fail to penetrate indoor environments effectively, leading to inaccuracies in identifying specific locations and interacting with virtual objects in real-world settings.
Innovation Solution
The implementation of AI-driven image processing and machine-learning classifiers within AR systems to recognize physical objects and environments, allowing for the generation of interactive narratives and virtual interactions that adapt based on recognized objects, user actions, and ambient conditions, thereby enhancing the AR experience by unifying interactivity between physical and virtual objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and traditional localization signals are used for indoor positioning, then outdoor localization accuracy is maintained, but indoor localization accuracy deteriorates due to signal penetration limitations
Solution Approach 1:
The patent introduces image processing and object recognition as intermediary technologies between the physical environment and the AR system. Instead of relying on GPS signals that cannot penetrate buildings, the system uses cameras to capture images and AI algorithms to recognize objects and infer location, serving as a mediator that enables indoor positioning without direct signal penetration
Solution Approach 2:
The patent replaces the electromagnetic signal-based GPS localization system with an image-based recognition system. The mechanical/optical system (camera capturing light reflected from objects) substitutes for the electromagnetic wave system (GPS signals), enabling localization through visual information rather than radio signal propagation
2Measurement precision
If AI-driven image processing is implemented to recognize objects indoors, then indoor localization accuracy is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent makes the camera and image processing system serve multiple functions: it captures images for localization, identifies objects for contextual information, recognizes environments for navigation, and provides visual feedback for AR overlay. This multi-functionality reduces the need for separate specialized sensors and systems, thereby limiting the increase in overall device complexity while improving localization accuracy
3Adaptability or versatility
If object recognition is used to enable interactive narratives, then user experience and immersion are improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-training machine learning models with extensive image datasets and pre-processing images to extract key features before full object recognition is required. The system performs initial image capture and preprocessing in advance, preparing data structures and identifying potential objects before the interactive narrative fully engages, thereby reducing real-time processing requirements
Data Source
AI summary
Systems and methods of using augmented reality (AR) with object recognition (OR) in a physical environment to advance a narrative may be provided. For example, the system may access narrative data representing the narrative. The system may, for a first node of the one or more nodes: generate a user interface associated with the narrative for the first node and access a first decision rule specifying a first physical object to be recognized to advance past the first node in the narrative. The system may further perform image recognition on an image of the physical environment, determine that the first physical object is in the physical environment based on the image recognition, transition from the first node in the narrative based on the first decision rule and the determination, and update the user interface to a second node in the narrative based on the transition from the first node.