지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
In this paper we propose a computationally efficient moving object tracking algorithm with CAMSHIFT Embedded Kalman Filter technique. Object tracking using CAMSHIFT still is suffering from fundamental problems such as cluttered background, occlusion and dynamic movement of objects. In order to cope with these problems, the Kalman filter is applied in CAMSHIFT to predict the location of object for efficient object tracking. As Kalman Filter is a set of mathematical equation, so it increases the computational complexity of our propose system. We solve this problem by using random frame selection procedure. We randomly select some frame instead of processing every frame for reducing the computational complexity. The experimental results are shown to prove the robustness, computational efficient and validity of the propose algorithm using various video sequences of moving object.
목차
Abstract
1. Introduction
2. Basic Frameworks
3. Experimental result
4. Conclusion
Reference
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