Object Tracking via Visible and Infrared Modality Switching
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Solution Overview
Problem
Existing object tracking systems face challenges in accurately tracking objects in varying lighting conditions and environments, such as low illumination or the presence of obstacles like glasses, which can affect the reliability of visible light images and lead to inaccuracies in 3D image generation.
Innovation Solution
The system employs a method that detects a target object in both visible light and infrared (IR) images, switching between modalities based on the reliability of the input images. It uses a camera without an IR-cut filter to capture IR images and activates an IR light source when necessary, ensuring accurate tracking by adapting to different lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visible light imaging is used for object tracking, then the system can operate in normal lighting conditions, but tracking accuracy deteriorates in low illumination or when obstacles like glasses are present
Solution Approach 1:
The system dynamically switches between visible light and infrared imaging modalities based on real-time reliability assessment. When visible light images show low reliability (detected through comparison with database images), the system transitions to infrared imaging, and vice versa. This dynamic adaptation ensures continuous high-quality tracking across varying environmental conditions.
Solution Approach 2:
The system changes the wavelength parameter of the input images by switching between visible light and infrared bands. This parameter change allows the system to overcome limitations of single modality, as infrared imaging provides reliable tracking in low illumination conditions where visible light fails, and visible light provides clearer images when infrared reliability is low.
2Reliability
If a single imaging modality is used, then the device complexity is reduced, but the reliability of tracking deteriorates in varying environmental conditions
Solution Approach 1:
The system implements multi-functionality by integrating both visible light and infrared imaging capabilities within a single tracking system. The camera can capture images in both wavelength bands, and the system universally handles both modalities through a unified processing framework that compares reliability and selects the appropriate input, making the system adaptable to all lighting conditions without requiring separate dedicated systems.
Solution Approach 2:
The system introduces an intermediary reliability assessment mechanism that compares current images with database images to determine which imaging modality (visible light or infrared) should be used for tracking. This intermediary evaluation layer mediates between the two imaging sources, selecting the most reliable input without requiring complex manual intervention or system reconfiguration.
3Measurement precision
If infrared imaging is used to improve low illumination tracking, then tracking accuracy improves in dark conditions, but visibility deteriorates when infrared light source is not activated
Solution Approach 1:
The system employs feedback through continuous reliability assessment, comparing current images with stored database images to evaluate the quality and reliability of the current imaging modality. When infrared images show low reliability (perhaps due to insufficient IR light source activation or poor infrared conditions), the feedback mechanism triggers a switch to visible light imaging, ensuring the system always operates with the most reliable modality available.
Solution Approach 2:
The system dynamically adjusts the imaging modality based on real-time conditions. When infrared imaging provides sufficient illumination and reliability, the system uses infrared input for tracking; when infrared illumination is insufficient or reliability drops, the system transitions to visible light imaging. This dynamic adjustment ensures optimal tracking precision across all lighting conditions.
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 enhances the accuracy and reliability of object tracking by leveraging the strengths of both visible light and IR imaging, effectively addressing the limitations of single-modality systems and ensuring robust performance across diverse environments.
Implementation Method 1
the second-type input image being based on light in a second wavelength band, different than the first wavelength band... The first wavelength band may include visible light and the second wavelength band may include infrared (IR) light
Data Source
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AI summary
An object tracking method and apparatus are provided. The object tracking method includes detecting a target object in a first-type input image that is based on light in a first wavelength band, tracking the target object in the first-type input image based on detection information of the target object, measuring a reliability of the first-type input image by comparing the first-type image to an image in a database, comparing the reliability of the first-type input image to a threshold, and tracking the target object in a second-type input image that is based on light in a second wavelength band.