원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.11 No.2
2016.02
pp.23-32
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
For moving objects detection, a background subtraction algorithm based on adaptive Gaussian mixture model is proposed in order to extract moving regions. The OTSU algorithm is researched in order to adapt to the changes in the background images; In order to accelerate model updating rate, a novel mechanism is the combination of expected sufficient statistics and L-recent window.
목차
Abstract
1. Introduction
2 The Traditional Detection Method
2.1 Optical Flow
2.2 Frame Subtraction
2.3 Background Subtraction
3. The Proposed Motion Object Detection Method
3.1 Create Background Model with GMM
3.2 Background Updating Criteria
3.3 Selection of OTSU Threshold
3.4 Analysis of Connected Areas
4. Experimental Analysis and Results
4.1 Detection of Motion Targets
4.2 Evaluation of Quality
5. Conclusion
References
1. Introduction
2 The Traditional Detection Method
2.1 Optical Flow
2.2 Frame Subtraction
2.3 Background Subtraction
3. The Proposed Motion Object Detection Method
3.1 Create Background Model with GMM
3.2 Background Updating Criteria
3.3 Selection of OTSU Threshold
3.4 Analysis of Connected Areas
4. Experimental Analysis and Results
4.1 Detection of Motion Targets
4.2 Evaluation of Quality
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보