QUT ePrints

Vision-Based UAV Maritime Search and Rescue Using Point Target Detection

Westall, Paul, Carnie, Ryan J., O'Shea, Peter J., Hrabar, Stefan, & Walker, Rodney A. (2007) Vision-Based UAV Maritime Search and Rescue Using Point Target Detection. In AIAC12 - Twelfth Australian International Aerospace Congress, Twelfth Australian Aeronautical Conference, 19-22 March 2007, Melbourne, Australia.

Abstract

Human maritime search and rescue missions have always been challenging and an element of chance is involved in the detection of survivors at sea. This research is proposing the use of machine vision to assist UAVs to increase the chances of success in locating humans lost at sea.

This paper presents an application of current image processing methods for target detection in a synthetic maritime scenario. An evaluation of the algorithm’s performance is also provided. The difficulties faced in the automatic detection of human targets in a maritime search environment are also considered.

The paper concludes that there is a range of greyscale intensities, approximately 26% based on current data set, where the target was unable to be detected which may limit the applicability of the algorithm. The effect on performance of target intensity level, threshold and forgetting factor are also investigated.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

630 since deposited on 21 Feb 2008
149 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 12579
Item Type: Conference Paper
Additional URLs:
Keywords: Maritime Search and Rescue, Computer Vision, Machine Vision, Mathematical Morphology, Dynamic Programming
ISBN: 9780980321500
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aerospace Engineering not elsewhere classified (090199)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2007 (please consult author)
Deposited On: 21 Feb 2008
Last Modified: 29 Feb 2012 23:37

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page