Animal Tracking in Infrared Video based on Adaptive GMOF and Kalman Filter

• 발행기관: 한국스마트미디어학회
• 저자명: Van Khien Pham Guee Sang Lee
• 간행물 정보: 『스마트미디어저널』Vol5, No.1, 1~10쪽, 전체 10쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2016.03.30

영문 초록

The major problems of recent object tracking methods are related to the inefficient detection of moving objects due to occlusions, noisy background and inconsistent body motion. This paper presents a robust method for the detection and tracking of a moving in infrared animal videos. The tracking system is based on adaptive optical flow generation, Gaussian mixture and Kalman filtering. The adaptive Gaussian model of optical flow (GMOF) is used to extract foreground and noises are removed based on the object motion. Kalman filter enables the prediction of the object position in the presence of partial occlusions, and changes the size of the animal detected automatically along the image sequence. The presented method is evaluated in various environments of unstable background because of winds, and illuminations changes. The results show that our approach is more robust to background noises and performs better than previous methods.

목차

I. INTRODUCTION

II. PROPOSED METHOD

II. EXPERIMENTAL RESULTS

III. CONCLUSION

키워드

Gaussian mixture model animal tracking foreground detection optical flow Kalman filter