中国科学技术大学 自动化系,安徽,合肥,230027
纸质出版:2017
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沈旭东, 蒋婷, 朱明. 稀疏样本人脸检索方法研究[J]. 微电子学与计算机, 2017, 34(1): 81-84.
SHEN Xu-dong, JIANG Ting, ZHU Ming. Approach on Sparse Samples Face Retrieval[J]. 2017, 34(1): 81-84.
提出一种将Gabor
LGBP
LPQ三种特征融合的人脸特征描述方法.将人脸按五官进行分块
分别提取Gabor
LGBP和LPQ特征
再通过融合得到最终的融合特征来表征每一个人脸.实验表明
在FERET
AT%T数据集以及在网吧采集的实际人脸数据集上
该融合特征检索性能与当前常用的特征相比有了一定程度的提高.
Face retrieval training samples is difficult to obtain in many situations. Therefore
an effective way to describe the human face becomes more important. We have fused Gabor feature
LGBP feature and LPQ feature to describe face in this paper. Faces are divided into blocks according to features
than fusion features obtained to characterize each individual face. Taken together
our results suggest that fused features for data retrieval have a certain improvement compared with the current popular features in FERET
AT%T database and ours dataset.
Samaria F, Young S. HMM-based architecture for face identification[J]. Image and vision computing, 1994, 12(8): 537-543. DOI: 537
Ji S, Zhang B, Du D, et al. Similarity Michaelis-Menten law pre-processing descriptor for face recognition[C]//Neural Networks (IJCNN), 2014 International Joint Conference on. Beijing: IEEE, 2014: 1272-1277.
Wang Z, Zhu M. Sparse representation-based face recognition for single example image per person[C]//Informatics in Control, Automation and Robotics. Berlin Heidelberg: Springer, 2011。
Kan M, Shan S, Su Y, et al. Adaptive discriminant analysis for face recognition from single sample per person[C]//Automatic Face % Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on. Santa Barbara: IEEE, 2011: 193-199.
Turk M, Pentland A. Eigenfaces for recognition[J]. Journal of Cognitive Neuroscience, 1991, 3(1): 71-86. DOI: 71
Deng W, Hu J, Guo J, et al. Robust, accurate and efficient face recognition from a single training image: A uniform pursuit approach[J]. Pattern Recognition, 2010, 43(5): 1748-1762. DOI: 1748
Phillips P J, Wechsler H, Huang J, et al. The FERET database and evaluation procedure for face-recognition algorithms[J]. Image and vision computing, 1998, 16(5): 295-306. DOI: 295
Majumdar A, Ward R. Pseudo-fisherface method for single image per person face recognition[C]//Acoustics, Speech and Signal Processing(ICASSP 2008), IEEE International Conference on. LasVegas, NV: IEEE, 2008: 989-992.
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