Vehicle Device Identification Using Facial and Iris Area Segmentation
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Solution Overview
Problem
Existing vehicle-mounted device identification systems face errors due to the small size of the pupil, leading to incorrect target selection and increased costs when using high-performance cameras or sophisticated image processing, which are not cost-effective.
Innovation Solution
A vehicle-mounted device identifying apparatus that uses a combination of facial direction and eyeball direction detection to accurately identify devices by dividing the eye into areas and recognizing the iris or pupil's position, reducing erroneous judgments and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the pupil is used for detection, then the detection target is small and detailed, but the detection accuracy decreases due to large errors
Solution Approach 1:
The eye is divided into multiple areas (first area, second area, third area) along the widthwise direction, with the central area serving as a reference. This segmentation allows the system to determine eyeball direction by comparing the iris or pupil position relative to these areas, improving detection reliability while maintaining simplicity
Solution Approach 2:
The iris is introduced as an intermediary detection target between the cornea reflection and the pupil. By detecting the iris position in addition to the pupil position, the system achieves more reliable eyeball direction detection without requiring high-performance cameras or complex image processing
2Measurement precision
If a high-performance camera is employed to achieve appropriate detection accuracy, then measurement precision improves, but equipment costs increase
Solution Approach 1:
The system uses standard camera performance combined with a multi-area division approach, achieving sufficient detection accuracy without requiring high-performance cameras. The face image is divided into multiple areas, allowing accurate eyeball direction detection with conventional imaging equipment
Solution Approach 2:
The detection space is segmented into multiple areas, transforming a complex high-precision detection problem into a simpler multi-region classification problem that can be solved with standard cameras and basic image processing
3Measurement precision
If sophisticated image processing sequences are employed, then measurement precision improves, but device complexity increases
Solution Approach 1:
The image processing is simplified by dividing the eye region into discrete areas and determining which area contains the iris or pupil. This segmentation approach replaces complex continuous image processing with simpler discrete region classification
Solution Approach 2:
The system processes only the necessary portions of the image (face and eye regions) at the required level of detail, avoiding unnecessary complex processing. The multi-area division provides sufficient precision without requiring sophisticated algorithms
Data Source
AI summary
If an iris or a pupil is detected as being positioned in a right area, a vehicle-mounted device identifier of a vehicle-mounted device identifying apparatus identifies a vehicle-mounted device group, which is disposed in an area that is on the right side of an area that is identified based on a facial direction detected by a facial direction detector. If the iris or the pupil is detected as being positioned in a left area, the vehicle-mounted device identifier identifies a vehicle-mounted device group, which is disposed in an area that is on the left side of an area that is identified based on the facial direction. If the iris or the pupil is detected as being positioned in a central area, the vehicle-mounted device identifier identifies a vehicle-mounted device group, which is disposed in an area that is identified based on the facial direction.