Image Integration By Airborne Optical Sectioning

Researchers have introduced a globally unique drone prototype to help search and rescue teams locate missing persons – even in dense forests. Subjects in individual thermal images often appear completely or partially hidden; the drone instead combines several individual images into one integral image (image integration) that can be used for classification and to better detect people.

As the image integration significantly reduce concealment, modern deep-learning methods can aid in correctly detecting individuals up to a probability of well over 90%. When using conventional individual images, the same procedure attains a recognition rate of less than 25%. As there is little to no data available to support this kind of classification, over the past few months, the team had to create its own training database.

Initial field study findings and pivotal early insight indicate that when it comes to concealed objects, image integration significantly supports classification purposes better than individual images.

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