Infrared Passenger Compartment Object Detection
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Solution Overview
Problem
Current digital imaging systems in vehicles face challenges in effectively detecting moving objects, particularly in low-light conditions, and distinguishing between moving and static objects to enhance image quality and safety features like driver alertness monitoring.
Innovation Solution
A computer-implemented method using infrared illumination and cameras, combined with object detection and machine-learning algorithms to identify and improve image quality of moving and static objects, and neural networks for classification, generating separate streams for dynamic and static objects to optimize resource usage and enhance image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If visible light illumination is used to improve image quality in the passenger compartment, then image brightness is improved, but driver distraction increases
Solution Approach 1:
The patent changes the wavelength/frequency of illumination from visible light to infrared light. This allows the illumination to be invisible to the human eye (avoiding driver distraction) while still enabling image capture by infrared-sensitive cameras, effectively resolving the contradiction between illumination needs and driver safety
2Measurement precision
If machine-learning algorithms are applied to all images in the stream to improve image quality, then image quality is improved, but computational resource consumption increases
Solution Approach 1:
The patent segments the image stream processing by applying machine-learning algorithms only to detected moving objects rather than processing all images uniformly. This selective approach maintains high image quality for relevant subjects while significantly reducing overall computational resource consumption by skipping static background processing
Solution Approach 2:
Instead of applying full image processing to every frame, the system applies partial processing only where necessary (on moving objects). This partial action principle optimizes the balance between image quality improvement and computational efficiency by avoiding redundant processing of static scenes
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
Enables accurate detection and classification of moving and static objects, improving image quality and safety features like driver alertness monitoring without distracting the driver, while efficiently using computational resources.
Implementation Method 1
illuminate the inside of the passenger compartment of the vehicle using an infrared light source
Implementation Method 2
The infrared light source may be, for example, an infrared LED
Implementation Method 3
obtain a stream of a plurality of consecutive images from the inside of the illuminated passenger compartment of the vehicle using an infrared camera
Implementation Method 4
The camera, which may be a CCD or CMOS camera, is adapted to capture images in the infrared spectrum
Data Source
AI summary
Disclosed are computer implemented methods for detecting a moving object in the passenger compartment of a vehicle. In an aspect, the method includes illuminating the inside of the passenger compartment of the vehicle using an infrared light source, obtaining a stream of a plurality of consecutive images from the inside of the illuminated passenger compartment of the vehicle using an infrared camera, identifying moving objects in the stream based on an object detection algorithm using a processor, and improving the image quality of the moving objects in the stream based on a machine-learning algorithm using the processor.