Driver Change Detection Using Interior Camera Head Absence
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Solution Overview
Problem
Existing driver monitoring systems using interior cameras struggle to reliably detect driver changes, especially when image-based face identification is unavailable, leading to poor performance and unnecessary re-initializations.
Innovation Solution
A method that detects driver changes by monitoring the absence of the driver's head within the camera's viewing range for defined time periods and lateral movements, allowing for standalone operation without additional sensors, and re-initializes the head model only when a change is confirmed, using the interior camera's data for reliable detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image-based face identification is used for driver change detection, then identification accuracy is improved, but system complexity increases due to requiring additional sensors or systems
Solution Approach 1:
The patent extracts the essential detection task from complex face identification systems and implements it using only the existing interior camera's head position detection capability. By taking out only the necessary function (detecting whether the head is in the viewing range) and removing unnecessary complexity (face identification algorithms, additional sensors), the system achieves driver change detection with the available resources.
Solution Approach 2:
The interior camera, already present for driver monitoring purposes, is made to serve the additional function of driver change detection. Instead of requiring separate identification systems, the existing camera infrastructure is utilized to its full potential by analyzing head presence in the viewing range, allowing the system to serve multiple functions with a single component.
2Measurement precision
If the head model is re-initialized frequently to ensure accurate tracking, then tracking precision is improved, but system performance deteriorates due to unnecessary re-initializations
Solution Approach 1:
The system continuously monitors the head position within the viewing range and uses this feedback to determine when re-initialization is actually necessary. By establishing a feedback loop that checks head presence status and only triggers re-initialization when the head is absent for a defined time period, the system avoids unnecessary re-initializations while maintaining tracking precision when needed.
Solution Approach 2:
The system performs preliminary detection of head absence before triggering re-initialization by monitoring for a defined time period. This preliminary action ensures that re-initialization occurs only when truly necessary (when the driver has actually changed), preventing premature or unnecessary re-initializations that would degrade system performance.
3Area of stationary object
If the viewing range is expanded to cover more area, then detection coverage is improved, but detection precision worsens due to reduced focus on the driver's head
Solution Approach 1:
The system uses partial action by focusing detection efforts only on the critical area where the driver's head should be present, rather than attempting to precisely detect heads throughout the entire expanded viewing range. The camera monitors the full area for safety purposes, but the driver change detection algorithm only needs to determine whether the head is within the expected viewing range portion, maintaining precision without requiring the entire area to be in sharp focus.
Data Source
AI summary
A method for identifying a driver change in a motor vehicle with the aid of an interior camera for monitoring the driver, which is characterized in that a driver change is detected when the head of the driver is not detected in the viewing range of the camera. In addition, a corresponding device and a computer program and a machine-readable memory medium are provided.