Abstract
Increasingly, multi-sensor systems are being developed to collect, process, and disseminate image and non-image data. Applications include homeland security, monitoring of facilities, and military situation assessment. Fusion of image and non-image data has traditionally been performed with extensive human-in-the-loop involvement. Typically the image data are used as the fundamental data source with non-image data simply overlaid on the image data, or conversely the non-image data are treated as fundamental, and the image data are used to confirm the identity of observed entities. This paper discusses the problem of multi-sensor fusion and argues that new techniques are emerging that allows fusion of image and non-image data at multiple levels of inference from the raw data level, to the feature level, decision-level, and knowledge level.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
