Deep Neural Networks for Head Pose Classification

被引：0

作者：

Lu, Yang ^{[1
]}

Yi, Shujuan ^{[1
]}

Hou, Nan ^{[2
]}

Zhu, Jingfu ^{[1
]}

Ma, Tiemin ^{[1
]}

机构：

[1] Heilongjiang Bayi Agr Univ, Coll Informat Technol, Daqing 163319, Peoples R China

[2] Northeast Petr Univ, Coll Elect & Informat Engn, Daqing 163318, Peoples R China

来源：

PROCEEDINGS OF THE 2016 12TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2016年

关键词：

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：

Head pose classification and estimation are essential for many face detection and recognition tasks and tracking applications. This paper proposes the robust and fast algorithms for head pose classification from labeled head pose database by employing deep neural networks (DNNs). The DNNs have capabilities to learn from raw images and process large-scale training image datasets. The proposed DNNs method has fast convergence and higher learning ability. The experimental results show that the proposed method outperforms existing methods in accuracy and robustness.

引用

页码：2787 / 2790

页数：4

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