Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Reduction of false alarms triggered by spiders/cobwebs in surveillance camera networks.

Hebbalaguppe, Ramya, McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477, Kuklyte, Jogile, Albatal, Rami orcid logoORCID: 0000-0002-9269-8578, Direkoglu, Cem and O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 (2016) Reduction of false alarms triggered by spiders/cobwebs in surveillance camera networks. In: IEEE International Conference on Image Processing, 25-28 Sep 2016, Phoenix, AZ. ISBN 978-1-4673-9661-6/16

Abstract
The percentage of false alarms caused by spiders in automated surveillance can range from 20-50%. False alarms increase the workload of surveillance personnel validating the alarms and the maintenance labor cost associated with regular cleaning of webs. We propose a novel, cost effective method to detect false alarms triggered by spiders/webs in surveillance camera networks. This is accomplished by building a spider classifier intended to be a part of the surveillance video processing pipeline. The proposed method uses a feature descriptor obtained by early fusion of blur and texture. The approach is sufficiently efficient for real-time processing and yet comparable in performance with more computationally costly approaches like SIFT with bag of visual words aggregation. The proposed method can eliminate 98.5% of false alarms caused by spiders in a data set supplied by an industry partner, with a false positive rate of less than 1%
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Spider detection; False alarm reduction; Computer Vision; Surveillance; Descriptor fusion
Subjects:Engineering > Imaging systems
Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: Proceedings IEEE International Conference on Image Processing. . IEEE. ISBN 978-1-4673-9661-6/16
Publisher:IEEE
Official URL:http://dx.doi.org/10.1109/ICIP.2016.7532496
Copyright Information:© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Funders:Enterprise Ireland, Science Foundation Ireland
ID Code:21420
Deposited On:05 Oct 2016 14:13 by Noel Edward O'connor . Last Modified 19 May 2021 11:37
Documents

Full text available as:

[thumbnail of ICIP_HEBBALAGUPPE_ET_AL_VER4.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
6MB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record