Head Detection by the Adaboost Algorithm for Head Pose Estimation

Xiang Yang Liu; Shao Song Zhu; Su Qing Wu; Zhi Wei Shen

doi:10.4028/www.scientific.net/AMM.427-429.1696

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429Head Detection by the Adaboost Algorithm for Head...

Head Detection by the Adaboost Algorithm for Head Pose Estimation

Abstract:

For human head pose analysis based on videos, pose is usually estimated on the head patch provided by a tracking module. However, head tracking is very sensitive to the large changes of pose. Therefore, this work locates the head patch in the videos by head detection. Firstly, we use the Adaboost algorithm to detect the human head in the video. Secondly, we present a dimensionality reduction method to process the head patch. Finally, we use the nearest neighbor method to estimate the head pose. The experiment results show: accurate head detecting helps to estimate the head pose. This method can be used for complex conditions of accurate head pose estimation.

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Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

1696-1699

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.1696

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Online since:

September 2013

Authors:

Xiang Yang Liu*, Shao Song Zhu, Su Qing Wu, Zhi Wei Shen

Keywords:

Adaboost, Dimensionality Reduction, Head Detection, Pose Estimation

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* - Corresponding Author

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