Acquiring/Recognising Eyes TRIZ Cases
- Pupil Dilation Detection for Deception Screening
Automated image sensors monitor pupil dilation differences from controlled audio stimuli, overcoming polygraph intrusiveness and false positives.
- Iris Capture Camera Positioning via Specularity Feedback
A camera system calculates its position relative to an eye using corneal light reflections for consistent image capture.
- Parallel CPU GPU Facial Recognition for Mobile Terminal Speed
Parallel CPU and GPU processing accelerates facial recognition by executing feature matching and liveness detection simultaneously, reducing execution time.
- Vehicle Visual Line Detection Automatic Calibration
Automatic calibration uses infrared gaze detection to update reference values, resolving complexity from manual posture changes.
- Inlier Neural Network for Eye Biometric Authentication Accuracy
An inlier neural network processes eye interest point pairs to generate reliability scores, filtering false positives from inconsistent spatial matches.
- Line-of-Sight Detection Using Adaptive Pupil and Iris Edge Processing
Adaptive line-of-sight detection switches between pupil and iris outline processing based on edge presence, resolving accuracy loss in bright pupil states.
- Line of Sight Detection Using Pupil-Face Correlation
Correlating pupil position, face direction, and eye outline shape resolves measurement precision errors caused by variations in user head pose.
- Multi-Sensor Iris Capture System for High-Resolution Authentication
Segmenting the field of view across multiple sensors maintains measurement precision while accommodating subject movement and wide coverage.
- Eye Gaze Tracking for Online Test Integrity
Automated eye gaze tracking monitors student attention during online examinations to verify identity and detect cheating behaviors.