Institutions | About Us | Help | Gaeilge
rian logo

Go Back
Reduction of false alarms triggered by spiders/cobwebs in surveillance camera networks.
Hebbalaguppe, Ramya; McGuinness, Kevin; Kuklyte, Jogile; Albatal, Rami; Direkoglu, Cem; O'Connor, Noel E.
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%
Keyword(s): Imaging systems; Image processing; Spider detection; False alarm reduction; Computer Vision; Surveillance; Descriptor fusion
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Hebbalaguppe, Ramya, McGuinness, Kevin ORCID: 0000-0003-1336-6477 <>, Kuklyte, Jogile, Albatal, Rami, Direkoglu, Cem and O'Connor, Noel E. ORCID: 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
Publisher(s): IEEE
File Format(s): application/pdf
Related Link(s):,
First Indexed: 2016-10-06 05:34:25 Last Updated: 2019-02-09 06:17:35