Eye Gaze Tracking via Surface Normal Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Vehicle operators often fail to properly scan their environment, leading to increased risk of accidents due to inadequate visual scanning behavior, which existing technologies have not effectively addressed.
Innovation Solution
A gaze tracking system that includes an image sensor device and a gaze analysis system to capture and analyze images of a vehicle operator's head, detect facial features, and determine gaze direction, providing real-time feedback on scanning behavior and generating reports on gaze distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used, then system complexity is low, but measurement precision of gaze direction is insufficient
Solution Approach 1:
The patent replaces complex mechanical gaze tracking systems with a computational approach using image sensors and surface normal calculations. Instead of mechanical eye trackers, the system uses standard image sensors to capture facial images and computationally determines gaze direction through surface normal identification of facial features, significantly reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent introduces surface normals as an intermediary computational element to bridge image data and gaze direction. By calculating surface normals from detected facial feature triangles and using their orientation to determine gaze direction, the system achieves accurate measurement without requiring complex direct tracking mechanisms.
2Reliability
If comprehensive environmental scanning is required, then safety improves, but driver workload increases
Solution Approach 1:
The patent implements a feedback system that provides real-time or near-real-time information about the driver's scanning behavior. The system analyzes gaze patterns and can alert drivers when they are not scanning the environment adequately, enabling them to self-correct without constant manual monitoring or complex controls, thus improving safety while maintaining ease of operation.
Solution Approach 2:
The system enables drivers to self-monitor and self-correct their scanning behavior through automated analysis and feedback. Rather than requiring external monitoring or complex driver actions, the system autonomously tracks gaze patterns and provides guidance, allowing drivers to maintain safety with minimal additional effort.
Data Source
AI summary
A gaze tracking system captures images of a vehicle operator. The gaze tracking system may detect facial features in the images and track the position of the facial features over time. The gaze tracking system may detect a triangle in an image, wherein the vertices of the triangle correspond to the facial features. The gaze tracking system may analyze the detected triangle to identify a surface normal for the triangle, and may track the surface normal (e.g., across multiple images) to track the eye gaze direction of the driver over time. The images may be captured and analyzed in near-real time. By tracking movement of the driver's head and eyes over time, the gaze analysis system may predict or estimate head position and/or gaze direction when one or more facial features are not detectable.