Augmented Reality Activity Solver Rectification
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Solution Overview
Problem
Current machine vision systems struggle to generate augmented reality interfaces for generic activities performed on various surfaces without requiring specific knowledge of image processing or machine vision techniques, limiting their applicability to specific activities.
Innovation Solution
A system and method that selects an activity solver library and configuration information to create an augmented reality display, involving rectification of the surface image, determination of activity state information, and rendering of solution information, allowing for generic activity support by mapping surface points and processing fixed locations to generate an augmented reality interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine vision systems use pre-determined image processing techniques for specific activities, then measurement precision and reliability are improved, but adaptability to generic activities deteriorates
Solution Approach 1:
The system implements a universal activity solver library that can handle multiple generic activities (board games, puzzles, card games) through a common image processing framework. The rectification module and state determination module are designed to work across different activity types by mapping various game surfaces to standardized coordinate systems, enabling one system to serve multiple functions without requiring activity-specific customization.
Solution Approach 2:
The system changes parameters such as perspective transformation matrices, coordinate mapping relationships, and feature detection thresholds to adapt to different activity types. By adjusting these parameters rather than rewriting the entire image processing pipeline, the system maintains high precision for each specific activity while remaining adaptable to generic activities through parameter reconfiguration.
2Measurement precision
If machine vision systems are designed for specific activities with specialized processing, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the image processing task into distinct modular components: perspective rectification module, feature detection module, state determination module, and solution rendering module. Each module performs a specific function independently, which reduces overall system complexity while maintaining high precision through specialized processing in each segment. The modular architecture allows independent optimization of each component without increasing overall complexity.
Solution Approach 2:
The system introduces intermediate representation layers between the raw image input and the final activity recognition output. The rectified image serves as an intermediary that standardizes different perspectives, and the determined state information acts as an intermediary that bridges image features and solution determination. These intermediaries simplify the processing pipeline by breaking down complex transformations into manageable steps.
3Speed
If the system processes images without rectification for various perspectives, then processing speed is improved, but measurement precision deteriorates
Solution Approach 1:
The system performs perspective rectification as a preliminary step before conducting detailed feature analysis and state determination. By pre-processing the image to establish correct geometric relationships and map surface points to their expected positions, the system ensures high measurement precision in subsequent processing steps. This preliminary action prevents the need for repeated corrections and maintains processing efficiency.
Data Source
AI summary
Systems and methods for generating an augmented reality interface for generics activities are disclosed. The systems and methods may be directed to creating an augmented reality display for an activity performed on a surface. Given an image of the activity, an activity solver library and associated configuration information for the activity may be selected. The surface of the activity from the image may be rectified, forming a rectified image, from which activity state information may be extracted using the configuration information. The activity state information may be provided to the activity solver library to generate solution information, and elements indicating the solution information may be rendered in a perspective of the original image. By providing the configuration information associated with an activity solver library, an augmented reality interface can be generated for an activity by capturing an image of the activity.