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Automatic population counts for improved wildlife management using aerial photography

Sirmacek, Beril and Wegmann, Martin and Reinartz, Peter and Dech, Stefan (2012) Automatic population counts for improved wildlife management using aerial photography. In: iEMSs Proceedings 2012, pp. 1-8. IEMSS 2012, 2012-07-01 - 2012-07-05, Leipzig, Deutschland. ISBN 9788890357428.

Full text not available from this repository.

Official URL: http://www.iemss.org/society/index.php/iemss-2012-proceedings


For effective conservation management, it is very important to provide accurate estimates of animal populations with certain time intervals. So far many studies are performed visually/manually which requires much time and is prone to errors. Besides, only a limited area can be considered for counting because of the effort required. In order to bring a new solution to this problem, herein we propose a novel approach for counting animals from aerial images by using computer vision techniques. To do so, we apply a probabilistic framework on local features in the image whose spectral reflectance differs from the surrounding region. We use mean shift segmentation and obtain probability density function (pdf) to detect focus of attention regions (FOA). Finally, we benefit from graph theory to detect segments which should represent animals. We test the feasibility of the proposed approach using aerial images of varying quality and angles (including orthogonal time lapse photography) from several different terrestrial ecosystems. Monitored species include birds and mammals. The algorithms successfully detect and count animals and provide a replicable and objective method for estimating animal abundance, however the methodology still requires estimates of error to be incorporated. This approach highlights how technical innovations in remote sensing can provide valuable information for conservation management.

Item URL in elib:https://elib.dlr.de/79188/
Document Type:Conference or Workshop Item (Speech, Paper)
Title:Automatic population counts for improved wildlife management using aerial photography
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Wegmann, MartinUniversität WürzburgUNSPECIFIEDUNSPECIFIED
Reinartz, PeterUNSPECIFIEDhttps://orcid.org/0000-0002-8122-1475UNSPECIFIED
Date:July 2012
Journal or Publication Title:iEMSs Proceedings 2012
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-8
EditorsEmailEditor's ORCID iDORCID Put Code
Keywords:Aerial imagery, Local Feature Extraction, Probability Density Function, Mean-Shift Segmentation, Graph Theory, Graph-Cut, Animal Detection, Animal Counting
Event Title:IEMSS 2012
Event Location:Leipzig, Deutschland
Event Type:international Conference
Event Start Date:1 July 2012
Event End Date:5 July 2012
Organizer:International Environmental Modelling & Software Society
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Projekt VABENE (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Leitungsbereich DFD
Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Reinartz, Prof. Dr.. Peter
Deposited On:29 Nov 2012 14:07
Last Modified:24 Apr 2024 19:45

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