| Title |
Livestock Theft Detection System Using Skeleton Feature and Color Similarity |
| Authors |
김준형(Jun Hyoung Kim) ; 주영훈(Yung Hoon Joo) |
| DOI |
http://doi.org/10.5370/KIEE.2018.67.4.586 |
| Keywords |
Skeleton feature ; Color similarity ; Object classification ; Livestock ; Multiple moving object ; Theft Detection System |
| Abstract |
In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method. |