Deploying speaker verification techniques to vision-based RPA detect and avoid

Martin, T.L. & McFadyen, A. (2015) Deploying speaker verification techniques to vision-based RPA detect and avoid. In 2015 International Conference on Unmanned Aircraft Systems (ICUAS), 9 - 12 June 2015, Denver, Colorado.

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Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

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ID Code: 94447
Item Type: Conference Paper
Refereed: Yes
Keywords: See and Avoid, Unmanned Aircraft, Computer Vision, Verification and Validation, Detection Error Trade-off (DET)
DOI: 10.1109/ICUAS.2015.7152343
ISBN: 9781479960095
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 IEEE
Deposited On: 05 Apr 2016 23:31
Last Modified: 07 Apr 2016 00:13

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