Object compressive tracking via online feature selection

被引：0
|
作者：
College of Internet of Things Engineering, Hohai University, Changzhou [1 ]
213022, China
不详 [2 ]
213022, China
机构：
来源：
Zidonghua Xuebao Acta Auto. Sin. | / 11卷 / 1961-1970期
关键词：
Bayesian classification models - Compressive sensing - High dimensional feature - Low computational complexity - Online feature selection - Real-time object tracking - Scale change - State-of-the-art algorithms;
D O I：
10.16383/j.aas.2015.c140809
中图分类号：
学科分类号：
摘要：
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