Improved Vehicle Speed Estimation Using Gaussian Mixture Model and Hole Filling Algorithm

被引：0
|
作者：
Nurhadiyatna, A. [1 ]
Hardjono, B. [1 ]
Wibisono, A. [1 ]
Sina, I. [1 ]
Jatmiko, W. [1 ]
Ma'sum, M. Anwar [1 ]
Mursanto, P. [1 ]
机构：
[1] Univ Indonesia, Fac Comp Sci, Depok, Indonesia
来源：
2013 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND INFORMATION SYSTEMS (ICACSIS) | 2013年
关键词：
BACKGROUND SUBTRACTION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Vehicle speed estimation using Closed Circuit Television (CCTV) is one of the interesting issues in the field of computer vision. Various approaches are used to perform automation in vehicle speed estimation using CCTV. In this study, the use of Gaussian Mixture Model (GMM) for vehicle detection has been improved with the hole-filling method (HF). The speed estimation of the vehicles with various scenarios has been done, and gives the best estimation with the deviation of 7.63 Km/hr. GMM fusion with hole-filling algorithm combined with Pinhole models have shown the best results compared with results using other scenarios.
引用
收藏
页码：451 / 456
页数：6
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