Multi-modal Camera Localization with Dynamic Mode Switching
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Solution Overview
Problem
Conventional camera localization systems in virtual reality and 3D gaming rely on single modes of data collection and analysis, leading to failures that interrupt the user experience.
Innovation Solution
A multi-modal real-time camera localization system that conducts quality assessments of depth, color, and inertia localization modes, automatically switching between them based on confidence thresholds and failure detection to ensure robust mapping between physical and virtual environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single mode of data collection and analysis is used for camera localization, then the system complexity is reduced, but the reliability deteriorates due to failures that interrupt user experience
Solution Approach 1:
The patent combines multiple localization modes (depth-based, color-based, and inertia-based) into a unified camera localization system. The quality manager integrates assessments from all three modes, and the mode controller synthesizes their results to select the most appropriate mode, thereby improving reliability through redundancy while managing complexity through structured integration.
Solution Approach 2:
The camera localization system is designed to perform multiple localization functions using different data modalities. The system can switch between depth-based localization, color-based localization, and inertia-based localization depending on environmental conditions, making the system universally applicable across diverse scenarios while maintaining reliability.
2Reliability
If multiple localization modes are implemented with quality assessment and automatic switching, then the reliability is improved, but the device complexity increases
Solution Approach 1:
The localization system is segmented into distinct functional modules: a quality manager that independently assesses each localization mode, a mode controller that makes switching decisions, and separate processing pipelines for depth-based, color-based, and inertia-based localization. This modular segmentation improves reliability through redundancy while managing complexity by organizing functions into discrete, manageable units.
Solution Approach 2:
The system dynamically adjusts its localization approach by continuously assessing quality metrics and automatically switching between different localization modes based on current environmental conditions and data quality. This dynamic adaptation improves reliability by selecting the most appropriate mode in real-time while keeping the overall system architecture manageable through rule-based switching logic.
3Ease of operation
If conventional single-mode localization is used, then the ease of operation is maintained, but the user experience is interrupted by localization failures
Solution Approach 1:
The localization system performs self-assessment through the quality manager, which automatically evaluates the quality of depth data, color data, and inertia data. The mode controller then autonomously selects the most appropriate localization mode without user intervention, ensuring continuous reliable operation while maintaining ease of use through automated decision-making.
Solution Approach 2:
The system implements continuous feedback through quality assessment of localization data from multiple modes. The quality manager monitors data quality metrics, and this feedback drives the mode controller's switching decisions, ensuring the system adapts to changing conditions while maintaining uninterrupted user experience through automated reliability management.
Data Source
AI summary
Methods, apparatuses and systems may provide for conducting a quality assessment of a depth localization mode, a color localization mode and an inertia localization mode, and selecting one of the depth localization mode, the color localization mode or the inertia localization mode as an active localization mode based on the quality assessment. Additionally, a pose of a camera may be determined relative to a three-dimensional (3D) environment in accordance with the active localization mode.