Virtual Navigation Path Generation Using Statistical Interest Regions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Navigating complex 3D virtual spaces is challenging for users due to their size and complexity, as existing solutions are often linear and do not account for points of interest or alternative paths found by other users.
Innovation Solution
A method and system that collect navigational data from experienced users to identify points of interest, merge them into regions, and analyze interest paths statistically to determine preferred paths, which can then be used to generate walkthroughs that satisfy predefined constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If linear navigation solutions are used to assist users traverse 3D spaces, then the navigation path is simplified and easier to follow, but the solution fails to account for points of interest and alternative paths that may be worth viewing
Solution Approach 1:
The patent segments the navigation system into multiple path types (linear paths, interest paths, and preferred paths) that can be independently selected and combined. This allows the system to provide both simplified linear navigation and flexible alternative routes to points of interest, resolving the contradiction between ease of operation and path flexibility.
Solution Approach 2:
The system dynamically adjusts navigation paths based on user preferences, points of interest, and statistical analysis of user behavior. Rather than providing a fixed linear path, the system can adaptively generate multiple path options and switch between them based on real-time conditions, maintaining both simplicity and flexibility.
2Device complexity
If traditional navigation assistance is provided that only shows linear paths, then the navigation instructions are simple and direct, but the system ignores useful paths found by other experienced users
Solution Approach 1:
The system performs preliminary analysis of navigational data from experienced users before generating navigation instructions. By pre-processing and storing effective paths and points of interest discovered by experienced users, the system can quickly retrieve and present this knowledge without adding complexity to the real-time navigation interface, thus preventing loss of navigation knowledge while maintaining system simplicity.
Solution Approach 2:
The system copies and adapts proven navigation paths from experienced users into standardized format that can be easily integrated with linear navigation instructions. This allows valuable navigation knowledge to be preserved and reused without requiring complex original path generation algorithms, maintaining system simplicity while preventing knowledge loss.
3Measurement precision
If navigational data from multiple users is collected and analyzed to find preferred paths, then more accurate and useful navigation paths are identified, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent extracts only the essential and most relevant features from complex navigational data, such as key path segments, points of interest, and statistical preferences, rather than processing entire raw trajectory datasets. This extraction approach maintains high path accuracy by focusing on critical navigation information while significantly reducing data processing complexity and computational requirements.
Solution Approach 2:
The system transforms raw navigational data into standardized parameters and statistical measures that are easier to process and compare. By changing the representation of navigational data from detailed trajectory information to aggregated path metrics and preferences, the system achieves accurate path identification with reduced processing complexity.
Data Source
AI summary
Navigational data may be collected from experienced users and paths may be extracted from the navigational data. One or more points of interest may be identified in the navigational data and the points of interests may be merged into an interest region. The navigational data may be reviewed for interest paths between the interest regions. The collection of possible interest paths may be reviewed interest paths in view of statistical procedures and criteria to determine if the interest path is a preferred interest path. If the preferred interest path does not satisfy the predefined constraints, additional interest paths may be reviewed by substituting an additional interest path for the interest path and repeating the review the interest path analysis. If the preferred interest path satisfies predefined criteria, a walkthrough of the virtual world may be generated based on the preferred interest path.