Cluster Analysis Using Improved Fuzzy c-Means Clustering for Object Localization: Vision Based Ill Cattle Localization System

Author

Jieun Kim ; Woo Young Jung

Author_Institution

Dept. of IT Convergence, Daegu Gyeongbuk Inst. of Sci. & Technol.(DGIST), Daegu, South Korea

Volume

2

fYear

2012

fDate

12-15 Dec. 2012

Firstpage

271

Lastpage

274

Abstract

We propose an improved method to accurately localize objects from surveillance camera system. It includes clustering estimation method using clusters analysis and improved fuzzy c-means clustering. It is very useful for herds of cattle localization. Our evaluation shows high accuracy on datasets. Our dataset´s target is Korean cattle shed. It means that our method is utilized for surveillance system in Korean cattle shed.

Keywords

computer vision; estimation theory; farming; fuzzy set theory; pattern clustering; video surveillance; Korean cattle shed; clustering estimation method; fuzzy c-means clustering; object localization; surveillance camera system; surveillance system; vision based ill cattle localization system; Cameras; Clustering algorithms; Clustering methods; Cows; Object detection; Robustness; Surveillance; animal localization; cattle localization; cattle shed surveilance system;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Applications (ICMLA), 2012 11th International Conference on

Conference_Location

Boca Raton, FL

Print_ISBN

978-1-4673-4651-1

Type

conf

DOI

10.1109/ICMLA.2012.174

Filename

6406708