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JACIII Vol.21 No.3 pp. 448-455
doi: 10.20965/jaciii.2017.p0448
(2017)

Paper:

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Identity Verification Based on Facial Pose Pool and Bag of Words Model

Wangbin Chu and Yepeng Guan†

School of Communication and Information Engineering, Shanghai University
99 Shangda Road, BaoShan District, Shanghai, China

†Corresponding author

Received:
November 8, 2016
Accepted:
December 14, 2016
Online released:
May 19, 2017
Published:
May 20, 2017
Creative Commons License
Keywords:
identity verification, facial pose pool, incremental clustering, bag of words model, gaussian mixture model
Abstract
There are many challenges for face based identity verification. It is one of fundamental topics in image processing and video analysis, and so on. A novel approach has been developed for facial identity verification based on a facial pose pool, which is constructed in an incremental clustering way to find both facial spatial information and orientation diversity. Bag of words is selected to extract image features from the facial pose pool in affine SIFT descriptor. The visual codebook is generated in k-means and Gaussian mixture model. Posterior pseudo probabilities are used to compute the similarities between each visual word and corresponding local features for image representation. Comparisons with some state-of-the-arts have highlighted the superior performance of the proposed method.
Cite this article as:
W. Chu and Y. Guan, “Identity Verification Based on Facial Pose Pool and Bag of Words Model,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.3, pp. 448-455, 2017.
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