Please use this identifier to cite or link to this item: http://localhost:80/xmlui/handle/123456789/19063
Title: GOAT FLOCK SURVEILLANCE: A VIDEO ANALYTICS FRAMEWORK USING QUADCOPTER
Authors: K.A. Qazi
Z. Mehmood
T. Nawaz
H.A. Habib
Keywords: Animal detection
Haar transform
Ada Boost
Kanade-Lucas-Tomasi
Quadcopter
Issue Date: 9-Mar-2018
Publisher: Lahore: Pakistan Association For The Advancement Of Science
Citation: Qazi, K. A. (2018). Goat Flock Surveillance: A Video Analytics Framework Using Quadcopter. Pakistan Journal of Science, 70(1), 63-70.
Abstract: In the present study, goat flock surveillance algorithm using video analytics was determined. The surveillance video camera was mounted over a quadcopter camera, which captured the videos of flocks. A video analytics algorithm using Haar features and the Ada Boost classifier was performed. The technique for tracking of flocks is based on the Kanade-Lucas-Tomasi feature (KLT) tracker. The algorithm presented here allows goat flock surveillance without human guidance and was helpful in real-time monitoring and management of goat flocks. The proposed algorithm made monitoring of goat flocks economical and could be applied to any kind of animal flock in different environments. The qualitative and quantitative analysis carried out for successful goat etection demonstrated the efficiency of the proposed algorithm as compared to the state-of-the-art goat flock rveillance and detection algorithms. The proposed algorithm successfully tracked the goat with accuracy of 93%.
URI: http://142.54.178.187:9060/xmlui/handle/123456789/19063
ISSN: 0300-9877
Appears in Collections:Issue 01

Files in This Item:
File Description SizeFormat 
PJS-306-5590.htm129 BHTMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.