Improving driver pose estimation

被引：0

作者：

Watta, P ^{[1
]}

Hou, Y ^{[1
]}

Lakshmanan, S ^{[1
]}

Natarajan, N ^{[1
]}

机构：

[1] Univ Michigan, Dept Elect & Comp Engn, Vehicle Elect Lab, Dearborn, MI 48128 USA

来源：

IV'2002: IEEE INTELLIGENT VEHICLE SYMPOSIUM, PROCEEDINGS | 2002年

关键词：

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：

[it this paper, we consider the problem of estimating the pose of a driver from video data. We propose extensions to our previous eigenface and Fisherface-based methods to improve classification performance. In particular, a hybrid neural network/nearest neighbor algorithm is formulated for classification of frames. Experimental results show that the hybrid neural network outperforms the nearest neighbor classifier.

引用

页码：310 / 315

页数：6

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