Multimodal Imaging Sensor Calibration for Image Fusion
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Solution Overview
Problem
Existing systems lack an effective method for crowd pre-screening using passive millimeter wave sensors due to limitations such as low energy reception, blurry images, and the inability to scan multiple moving targets, making them unsuitable for heavy passenger traffic environments.
Innovation Solution
A multi-sensor system combining a passive millimeter wave sensor with RGB and thermal sensors, connected to a processing device with an image fusion module, analytic module, and alert triggering module, which transforms and fuses images to identify concealed objects across multiple frames, overcoming the limitations of passive millimeter wave sensors by analyzing time-lapse images and differentiating between human and non-human objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If passive millimeter wave sensors are used for crowd pre-screening, then security detection capability is improved, but image quality deteriorates due to low energy reception causing blurry images
Solution Approach 1:
The patent combines passive millimeter wave sensors with active millimeter wave sensors and other imaging sensors to create a multi-sensor fusion system. The active sensor compensates for the low energy reception of passive sensors, providing clear images while maintaining security detection capability. This merging resolves the contradiction by having each sensor type compensate for the other's weaknesses.
2Productivity
If passive millimeter wave sensors scan multiple moving targets, then crowd pre-screening efficiency is improved, but the ability to capture clear images deteriorates due to motion blur and low energy
Solution Approach 1:
The system merges passive millimeter wave sensors capable of scanning multiple moving targets with active millimeter wave sensors and other high-speed imaging sensors. The fusion of data from multiple sensors allows the system to maintain image clarity even when scanning moving targets, while improving overall crowd pre-screening efficiency through parallel processing.
Solution Approach 2:
The system performs preliminary calibration and synchronization of multiple sensors before actual scanning. This preliminary action ensures that when multiple moving targets are scanned simultaneously, the sensors are properly coordinated to capture clear images, preventing motion blur and maintaining image quality during high-speed scanning.
3Measurement precision
If multi-sensor fusion is implemented for accurate image fusion, then detection accuracy is improved, but system complexity increases due to calibration and data processing requirements
Solution Approach 1:
The patent implements preliminary calibration procedures for all sensors in the multi-sensor system before deployment. This preliminary action establishes accurate spatial relationships and synchronization between sensors, which simplifies subsequent data processing and fusion operations. The calibration data is stored and reused, reducing the complexity of real-time processing while maintaining high detection accuracy.
Data Source
AI summary
A system and a method for a crowd surveillance device comprising a multi-sensor system connected to a processing device, wherein the processing device comprises an image fusion module for receiving images from the multi-sensor system, transforming and fusing images into a fused image; an image analytic module for extracting each individual target and identifying any conceal object on the individual target, an alert triggering module for triggering an alert in the event a conceal object on the individual target is identified.