Entity Tracking via AR-Independent Feature Data URI
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Solution Overview
Problem
Current augmented reality applications face difficulties in developing and maintaining entity tracking functionality due to the need for multiple feature data generation algorithms and formats compatible with various augmented reality engines, leading to increased complexity and size of applications.
Innovation Solution
A method and apparatus for tracking entities in an augmented reality space using feature data independent of the augmented reality engine, where a uniform resource identifier (URI) is generated to acquire feature data from a resource server, allowing the AR engine to process and track entities without relying on engine-specific algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple feature data generation algorithms are included to support various AR engines, then compatibility with different AR engines is improved, but application complexity and size increase
Solution Approach 1:
The patent introduces a resource server as an intermediary component that stores feature data for multiple AR engines. Instead of embedding multiple feature data generation algorithms within the augmented reality application, the application generates URIs and retrieves pre-processed feature data from the resource server. This mediator approach allows the application to support multiple AR engines without increasing its own complexity or size.
Solution Approach 2:
The patent extracts the feature data generation and storage functionality from the augmented reality application itself and places it in a separate resource server. By taking out this complex functionality, the application becomes simpler and smaller while still maintaining the ability to support multiple AR engines through URI-based data retrieval.
2Reliability
If multiple feature data generation algorithms are included to support various AR engines, then tracking performance across different engines is improved, but development difficulty increases
Solution Approach 1:
The resource server acts as a mediator that handles the complexity of feature data generation and optimization for different AR engines. Developers only need to create URIs and retrieve appropriate feature data, without needing to understand or implement multiple complex algorithms, thus improving ease of development while maintaining tracking performance.
Solution Approach 2:
The system creates and stores copies of feature data in different formats optimized for different AR engines on the resource server. The application can then retrieve the appropriate copy based on the target AR engine, avoiding the need to implement multiple generation algorithms while ensuring optimal tracking performance for each engine.
3Measurement precision
If engine-specific feature data generation algorithms are used, then tracking accuracy for specific engines is improved, but code reuse and maintenance become difficult
Solution Approach 1:
The resource server mediates between the need for engine-specific optimized feature data and the desire for simple, maintainable application code. The application maintains simple, engine-agnostic URI generation and data retrieval logic, while the resource server handles the complexity of maintaining engine-specific feature data formats, enabling easy code reuse and maintenance.
Data Source
AI summary
A method and an apparatus for tracking an entity based on feature data independent of an augmented reality engine are provided. A URI for feature data of an entity is generated from a combination of a name of the entity and a name of an AR engine, feature data of the entity representing characteristics of the entity is acquired in a format capable of being processed by the AR engine by using the URI, the entity is tracked in an augmented reality space by executing the AR engine based on the acquired feature data, and thus, an entity based on feature data independent of an augmented reality engine may be tracked.