Adaptive Motion Reference Coordinates for Accurate Intent Recognition

The patent applies the dynamics principle by transitioning from a static preestablished spatial coordinate system to a dynamic motion reference spatial coordinate system that adapts in real-time. The system dynamically establishes coordinate systems based on user motion characteristics, gaze direction, and environmental context, allowing the coordinate framework itself to evolve during operation. This resolves the contradiction by making the coordinate system flexible enough to maintain recognition accuracy while adapting to changing user characteristics and environmental conditions.

The patent implements parameter changes by modifying the fundamental parameters of the coordinate system (origin position, axis orientations, dimensionality) based on detected user motion patterns and gaze direction. Instead of using fixed coordinate parameters, the system continuously adjusts these parameters to match the dominant components of user motion, thereby maintaining high recognition accuracy across different user characteristics and environmental scenarios.

The system employs dynamics by making the coordinate framework adaptive rather than fixed. It dynamically adjusts the motion reference spatial coordinate system based on real-time detection of user gaze direction, motion patterns, and environmental context. This allows the system to automatically adapt to different users and motion characteristics without requiring complex manual configuration, thus maintaining ease of implementation while significantly improving adaptability.

The patent applies self-service by enabling the system to automatically establish and adjust its own coordinate system based on detected user behavior patterns. The system autonomously identifies dominant motion components, determines appropriate coordinate system dimensions and orientations, and adapts to different users without external intervention. This self-adjusting capability provides high adaptability while keeping the implementation process simple and automated.

The patent resolves this contradiction by implementing a dynamic coordinate system that can rapidly adapt to changing conditions. The motion reference spatial coordinate system is established and adjusted in real-time based on user gaze and motion detection, allowing the system to maintain both speed and accuracy. The dynamic nature enables quick response to environmental changes while preserving recognition precision through context-aware coordinate alignment.

The system applies preliminary action by pre-establishing the motion reference spatial coordinate system based on initial detection of user gaze direction and dominant motion components before full motion recognition begins. This preliminary setup optimizes the coordinate framework in advance, enabling both fast processing and accurate recognition from the outset, rather than requiring continuous adjustments during motion analysis.

The patent applies the extraction principle by isolating and focusing only on the dominant components of user motion rather than processing all three spatial dimensions equally. The system identifies and extracts the primary motion direction(s) based on gaze direction and motion analysis, then establishes a reduced-dimensional motion reference coordinate system that contains only the necessary dimensions for accurate recognition. This extraction of essential components maintains comprehensive representation of relevant motion while improving recognition efficiency by reducing unnecessary dimensional complexity.

The patent implements dimensionality change by dynamically adjusting the number of dimensions in the motion reference spatial coordinate system based on the actual motion characteristics. Instead of always using a fixed three-dimensional system, the system adapts the dimensionality to match the dominant components of motion (e.g., using one-dimensional or two-dimensional coordinate systems when motion is primarily linear or planar). This dynamic dimensionality adjustment maintains comprehensive motion representation while significantly improving recognition efficiency by reducing computational complexity.