Gaze and Pose Detection for Anticipating Operator Intent
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Solution Overview
Problem
Current systems for aircraft or vehicle cockpit interfaces can only detect interactions after they occur, lacking the ability to anticipate operator intent before control activation, which hinders the development of more intuitive user interfaces.
Innovation Solution
A system utilizing cameras to capture image streams of the operator, analyzing gaze direction and body pose to infer future interactions by mapping the position and orientation of cockpit interfaces, and assigning confidence levels to predicted focus targets, incorporating operational context and historical data for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera-based detection methods are used to detect operator interactions, then real-time detection capability is improved, but the ability to anticipate operator intent prior to interaction is lost
Solution Approach 1:
The system performs preliminary detection of gaze direction and body pose before the operator actually interacts with controls. By analyzing visual attention and physical orientation in advance, the system predicts which controls the operator will interact with next, enabling anticipatory UI responses and reducing reaction time.
Solution Approach 2:
Instead of detecting interactions after they occur through traditional methods, the system inverts the approach by detecting precursors to interaction (gaze and pose) and predicting future interactions. This inversion transforms post-interaction detection into pre-interaction anticipation.
2Measurement precision
If multiple cameras and sensors are deployed to improve detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs multi-functional cameras that simultaneously capture both facial features for gaze detection and body features for pose estimation. This universal approach allows a single camera system to perform multiple detection functions, reducing the need for separate specialized sensors and thereby limiting complexity growth.
Solution Approach 2:
The system merges gaze detection and body pose estimation into a unified analysis framework. By combining these detection functions and processing them together through integrated algorithms, the system achieves improved accuracy while avoiding the complexity of completely separate detection and processing systems.
3Measurement precision
If comprehensive image analysis is performed to predict future interactions, then prediction accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The system performs partial image analysis by focusing specifically on key features relevant to prediction (gaze direction, body pose) rather than analyzing all image data comprehensively. This selective approach achieves sufficient prediction accuracy while reducing computational burden and processing time.
Solution Approach 2:
The system skips detailed comprehensive analysis in favor of rapid detection of critical features. By prioritizing speed and focusing only on the most important predictive features, the system achieves real-time prediction capability without excessive processing delays.
Data Source
AI summary
A system and method for inferring operator intent by detecting operator focus incorporates cameras positioned within a cockpit or control space of a vehicle and oriented at an operator of the vehicle. The cameras capture images of the operator in a control seat; the images are analyzed (either individually or sequentially) to determine a gaze and/or body pose of the operator (including, e.g., a position and orientation of the torso and limbs). By comparing the determined gaze and/or body pose to the positions and orientations of potential focus targets within the control space (e.g., windows, display units, and/or control panels that the operator may engage with visually and/or physically), the system predicts the most likely future focus target or targets: what the operator is most likely to visually and/or physically engage with next. Operator intent may be further analyzed to identify potentially abnormal or anomalous behavior.