O'Keeffe, Simon and Villing, Rudi (2019) A Lightweight Region Proposal Network for Task Specific Applications. In: 30th Irish Signals and Systems Conference (ISSC), Maynooth, Ireland, 2019. IEEE. ISBN 978-1-7281-2800-9

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Abstract

Quickly and cheaply finding areas of interest within an image can save computationally intensive image processing in a vision pipeline. Existing region proposal networks are either too general (finding all objects in an image) or too complex (providing fine-tuned bounding boxes for classification). We propose a straightforward region proposal network that simply scores parts of the image based on whether or not they contain an object of interest. This calculation can be carried out quickly and for many applications including autonomous driving only a small fraction of the image area may contain objects of interest. We trained our network on an autonomous robot soccer dataset with similar characteristics to the popular KITTI autonomous driving dataset and achieved a recall greater than 95% while eliminating on average over 80% of the image area from further processing.

Item Type:	Book Section
Keywords:	Region Proposal; convolutional Neural Networks; real-time; vision pipeline;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	13571
Identification Number:	https://doi.org/10.1109/ISSC.2019.8904949
Depositing User:	Rudi Villing
Date Deposited:	13 Nov 2020 16:12
Publisher:	IEEE
Refereed:	Yes
Funders:	Irish Research Council under their Government of Ireland Postgraduate Scholarship 2013, Science Foundation Ireland (SFI) under Grant Number 16/RI/3399
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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