Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/83883
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Type: Conference paper
Title: Bio-inspired feature extraction and enhancement of targets moving against visual clutter during closed loop pursuit
Author: Halupka, K.
Wiederman, S.
Cazzolato, B.
O'Carroll, D.
Citation: Proceedings of the 2013 20th IEEE International Conference on Image Processing, ICIP 2013, 2013 / pp.4098-4102
Publisher: IEEE
Publisher Place: online
Issue Date: 2013
Series/Report no.: IEEE International Conference on Image Processing ICIP
ISBN: 9781479923410
ISSN: 1522-4880
Conference Name: International Conference on Image Processing (20th : 2013 : Melbourne)
Statement of
Responsibility: 
Kerry J. Halupka, Steven D. Wiederman, Benjamin S. Cazzolato, David C. O‘Carroll
Abstract: We developed a biologically inspired model for detection and pursuit of small targets against complex backgrounds and tested it in a closed-loop flight arena. A winner-takes-all network of local feature detectors based on insect Small Target Motion Detector (STMD) neurons was used to direct the gaze of a camera mimicking the viewpoint of the pursuer in a series of small steps (saccades) whilst fixating the background. The output of a direction-selective network of 2nd order local motion correlators was then used to enhance the relative salience of features in the direction of travel of the winning feature. The combination of saccadic fixation and robust target-ground discrimination provided by the STMD front-end, with an attention-like 2nd order salience enhancement provided very reliable capture of tiny targets even in visually challenging scenarios.
Rights: ©2013 IEEE
DOI: 10.1109/ICIP.2013.6738844
Published version: http://dx.doi.org/10.1109/icip.2013.6738844
Appears in Collections:Aurora harvest
Mechanical Engineering conference papers

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