Enhancing Long-Range Automatic Target Recognition Using Spatial Context

Iain Rodger, Rachael Abbott, Neil Robertson, Barry Connor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

This paper presents a high-performing automatic target recognition system which can be used for long-range surveillance scenarios. The main novelty of our system is that it uses contextual information from RGB images to help classify targets in long range real world LWIR images. This contextual framework provides additional information of an object's surrounding environment, leading to a significant increase in long-range target recognition accuracy. This work will be of interest to the defence community as a high-performing automatic recognition system is a highly sought-after capability.
Original languageEnglish
Title of host publication2017 Sensor Signal Processing for Defence Conference (SSPD)
Publisher IEEE
Number of pages6
ISBN (Electronic)978-1-5386-1663-5
ISBN (Print) 978-1-5386-1664-2
DOIs
Publication statusEarly online date - 21 Dec 2017
Event 2017 Sensor Signal Processing for Defence Conference - London, UK
Duration: 06 Dec 201707 Dec 2017

Conference

Conference 2017 Sensor Signal Processing for Defence Conference
Abbreviated titleSSPD
Period06/12/201707/12/2017

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  • Cite this

    Rodger, I., Abbott, R., Robertson, N., & Connor, B. (2017). Enhancing Long-Range Automatic Target Recognition Using Spatial Context. In 2017 Sensor Signal Processing for Defence Conference (SSPD) IEEE . https://doi.org/10.1109/SSPD.2017.8233231