Comparison of Two Methods for Stationary Incident Detection Based on Background Image

• 발행기관: 한국스마트미디어학회
• 저자명: DeepakGhimire Joonwhoan Lee
• 간행물 정보: 『스마트미디어저널』Vol1, No.3, 48~55쪽, 전체 8쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2012.09.30

영문 초록

In general, background subtraction based methods are used to detect the moving objects in visual tracking applications. In this paper we employed background subtraction based scheme to detect the temporarily stationary objects. We proposed two schemes for stationary object detection and we compare those in terms of detection performance and computational complexity. In the first approach we used single background and in the second approach we used dual backgrounds, generated with different learning rates, in order to detect temporarily stopped object. Finally, we used normalized cross correlation (NCC) based image comparison to monitor and track the detected stationary object in a video scene. The proposed method is robust with partial occlusion, short time fully occlusion and illumination changes, as well as it can operate in real time.

목차

Abstract

I. Introduction

II. Stationary Object Detection

III. NCC Based Stationary Object Monitoring

IV. Experimental Results and Discussion

V. Conclusion

References

키워드

Background Subtraction Temporarily Stationary Objects Normalized Cross Correlation Object Tracking Illegally Parked Vehicles