Multiple Person Tracking Using Omnidirectional Cameras

被引：0

作者：

Demiroz, Baris Evrim ^{[1
]}

Salah, Albert Ali ^{[1
]}

Akarun, Lale ^{[1
]}

机构：

[1] Bogazici Univ, Bilgisayar Muhendisligi Bolumu, TR-80815 Bebek, Turkey

来源：

2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2014年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Person tracking in videos is crucial in different areas such as security applications. In this work we present a method that first finds human presence probabilities on discrete locations via variational Bayesian inference using images obtained from omnidirectional cameras and then uses that information to solve the tracking problem as a flow optimization problem. In our experiments on the BOMNI dataset, we have increased tracking performance (MOTA) to %8639, which was reported as %68.18 using the baseline method.

引用

页码：1231 / 1234

页数：4

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