2-D Line Pattern Image Classification for Driver Attention
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Solution Overview
Problem
Current image classification systems for human identification and vehicle operator awareness require high computing power due to the need for high-quality image processing, which is affected by environmental variations and can produce false signals with crude measures like heart metric monitoring.
Innovation Solution
An image classification system that uses a light source to emit a 2-D line pattern, which is reflected and compared to previously obtained patterns in a database, reducing data processing requirements by using a 2-D line pattern representative of the target, such as a facial fingerprint, to classify the target's attention status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high quality image processing is used for human identification, then identification accuracy is improved, but computing power requirements increase
Solution Approach 1:
The patent extracts only the essential line pattern information from the full facial image, discarding redundant detail while preserving the unique identifying characteristics. This allows classification to proceed with minimal data, reducing computing power requirements while maintaining identification accuracy.
Solution Approach 2:
The patent segments the facial image into a simplified line pattern representation, separating the critical identifying features from the non-essential details. This segmentation enables processing with reduced computational complexity while preserving the necessary information for accurate classification.
2Measurement precision
If detailed facial feature recognition is used to determine driver awareness, then classification accuracy is improved, but processing capability requirements increase
Solution Approach 1:
The patent extracts only the line pattern information from detailed facial images, removing the need for complex processing of individual facial features. This extraction maintains classification accuracy while significantly reducing processing capability requirements.
Solution Approach 2:
The patent creates a simplified line pattern copy of the facial image that preserves the essential identifying characteristics without requiring processing of the original detailed image. This copy can be processed with minimal computational resources while maintaining classification accuracy.
3Device complexity
If crude measures like heart metric monitoring are used to monitor driver awareness, then system simplicity is improved, but reliability decreases due to false signals
Solution Approach 1:
The patent replaces physiological monitoring methods (heart metrics) with an optical imaging system that captures line patterns from facial reflections. This substitution eliminates false signals associated with crude physiological measures while maintaining system simplicity through the use of standard imaging components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces processing power and memory needs while providing accurate classification of vehicle occupants' attention levels with reduced false signals, enhancing system efficiency and reliability.
Implementation Method 1
at least one light source configured to emit light towards the target, wherein at least a portion of the emitted light is reflected by the target
Data Source
AI summary
An image classification system (100) configured to classify a target (118) and method (300) thereof is provided, wherein the system (100) includes at least one light source (102) configured to emit light with at least one line pattern (104) towards the target (118), wherein at least a portion of the emitted light and line pattern is reflected by the target (118). The system (100) further includes an imager (106) configured to receive at least a portion of the reflected light and line pattern, such that an obtained 2-D line pattern (116) is produced that is representative of at least a portion of the emitted light and line pattern reflected by the target (118), and a data processor (112) configured to compare the 2-D line pattern to at least one previously obtained 2-D line pattern stored in a database (110), such that the data processor (112) classifies the 2-D line pattern as a function of the comparison.