- 영문명
- People Detection Algorithm in Dynamic Background
- 발행기관
- 강원대학교 산업기술연구소
- 저자명
- 최유정(Yu Jung Choi) 이동렬(Dong Ryeol Lee) 김 윤(Yoon Kim)
- 간행물 정보
- 『산업기술연구』vol.38, 41~52쪽, 전체 12쪽
- 주제분류
- 공학 > 공학일반
- 파일형태
- 발행일자
- 2018.10.31
국문 초록
영문 초록
Recently, object detection is a critical function for any system that uses computer vision and is widely used in various fields such as video surveillance and self-driving cars. However, the conventional methods can not detect the objects clearly because of the dynamic background change in the beach. In this paper, we propose a new technique to detect humans correctly in the dynamic videos like shores. A new background modeling method that combines spatial GMM (Gaussian Mixture Model) and temporal GMM is proposed to make more correct background image. Also, the proposed method improve the accuracy of people detection by using SVM (Support Vector Machine) to classify people from the objects and KCF (Kernelized Correlation Filter) Tracker to track people continuously in the complicated environment. The experimental result shows that our method can work well for detection and tracking of objects in videos containing dynamic factors and situations.
목차
1. 서 론
2. 제안하는 방법
3. 실험 결과 및 고찰
4. 결 론
References
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