해변에서의 사람 검출 알고리즘

People Detection Algorithm in the Beach

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.

키워드

Object DetectionObject TrackingGMMBackground CutSVMKCF Tracker
제목
해변에서의 사람 검출 알고리즘
제목 (타언어)
People Detection Algorithm in the Beach
저자
최유정김윤
DOI
10.9717/kmms.2018.21.5.558
발행일
2018-05
유형
Y
저널명
멀티미디어학회논문지
21
5
페이지
558 ~ 570