arXiv:2606.13042v1 Announce Type: new Abstract: In intelligent video surveillance, cameras record image sequences during day and night. Commonly, this demands different sensors. To achieve a better performance it is not unusual to combine them. We focus on the case that a long-wave infrared camera records continuously and in addition to this, another camera records in the visible spectral range during daytime and an intelligent algorithm supervises the picked up imagery. More accurate, our task is multispectral CNN-based object detection. At first glance, images originating from the visible sp
The continuous advancements in AI and sensor technology, coupled with the increasing demand for robust surveillance systems, push for integrated solutions across spectral ranges.
Improved multispectral object detection enhances the reliability and effectiveness of surveillance, especially in challenging environments and conditions, with applications in both civilian and defense sectors.
This development allows for more accurate and resilient object detection in video surveillance by leveraging data from both visible and thermal spectra, overcoming limitations of single-spectrum systems.
- · AI/ML developers
- · Security solutions providers
- · Defence contractors
- · National security agencies
- · Criminal organizations operating at night
- · Legacy single-spectrum surveillance companies
Further integration of multispectral data will lead to more robust and less exploitable surveillance systems.
The enhanced surveillance capabilities could influence strategic defense planning and urban policing strategies.
Widespread deployment of such systems may raise new questions regarding privacy and ethical use of advanced surveillance technologies.
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Read at arXiv cs.AI