Objects Detection and Tracking in Highly Congested Traffic Using Compressed Video Sequences

被引：0
作者：
Bernas, Marcin [1 ]
机构：
[1] Silesian Tech Univ, Fac Transport, PL-40019 Katowice, Poland
来源：
COMPUTER VISION AND GRAPHICS | 2012年 / 7594卷
关键词：
ROBUST; ALGORITHM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper presents a model to detect and track vehicles in highly congested traffic using low quality (usually compressed) video sequences. Robustness of the model is provided by applying a data fusion for various detection and tracking algorithms. The surveys to find reliable detection algorithms were performed. Basing on the experiments, the model calibration and results were presented. The proposed model provides data, which can be used by traffic engineers in various microscopic traffic simulations.
引用
收藏
页码：296 / 303
页数：8
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