Martinez Dinnbier, Nuria (Cranfield University), THUEUX, Yoann (Airbus), Savvaris, Al (Cranfield University), Tsourdos, Antonios (Cranfield University)

Target Detection Using Gaussian Mixture Models and Fourier Transforms for UAV Maritime Search and Rescue

Scheduled for presentation during the "UAS Payloads" (FrC2), Friday, June 16, 2017, 16:20−16:40, Salon AB

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 23, 2024

Abstract

In the event of a maritime disaster, casualties need to be found and rescued promptly. Image processing methods could help to perform automated detection from a UAV. The main current approaches are divided between the use of multispectral and thermal cameras, which can deal with lightning difficulties but are expensive and present high noise problems; or the use of EO vision cameras. This paper presents a method combining both color analysis and frequency patterns identification using an inexpensive vision camera, and implements it through an adaptive algorithm to deal with a dynamically changing background. The method is tested successfully in different environments.