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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/5958

Title: A modified model for the Lobula Giant Movement Detector and its FPGA implementation
Authors: Meng, H
Appiah, K
Yue, S
Hunter, A
Hobden, M
Priestley, N
Hobden, P
Pettit, C
Keywords: Neural Networks
Bio-inspired vision chip
Embedded vision
Visual motion
FPGA
Publication Date: 2010
Publisher: Elsevier Inc
Citation: Computer Vision and Image Understanding, 114(11): 1238 - 1247, Nov 2010
Abstract: Bio-inspired vision sensors are particularly appropriate candidates for navigation of vehicles or mobile robots due to their computational simplicity, allowing compact hardware implementations with low power dissipation. The Lobula Giant Movement Detector (LGMD) is a wide-field visual neuron located in the Lobula layer of the Locust nervous system. The LGMD increases its firing rate in response to both the velocity of an approaching object and the proximity of this object. It has been found that it can respond to looming stimuli very quickly and trigger avoidance reactions. It has been successfully applied in visual collision avoidance systems for vehicles and robots. This paper introduces a modified neural model for LGMD that provides additional depth direction information for the movement. The proposed model retains the simplicity of the previous model by adding only a few new cells. It has been simplified and implemented on a Field Programmable Gate Array (FPGA), taking advantage of the inherent parallelism exhibited by the LGMD, and tested on real-time video streams. Experimental results demonstrate the effectiveness as a fast motion detector.
Description: Copyright @ Elsevier Inc. All rights reserved.
Sponsorship: UK Trade and Strategy Board under Grant TP/2/SC/6/1/10444.
URI: http://dl.acm.org/citation.cfm?id=1866598
http://bura.brunel.ac.uk/handle/2438/5958
DOI: http://dx.doi.org/10.1016/j.cviu.2010.03.017
ISSN: 1077-3142
Appears in Collections:Electronic and Computer Engineering
Publications
Dept of Electronic and Computer Engineering Research Papers

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