An Incremental Two-Dimensional Principal Component Analysis for Object Recognition
Joint Authors
Ge, Weimin
Sun, Mingyue
Wang, Xiaofeng
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-20
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Two-dimensional principal component analysis algorithm (2DPCA) can be performed in the batch mode and can not meet the real-time requirements of the video stream.
To overcome these limitations, the incremental learning of the candid covariance-free incremental PCA (CCIPCA) is innovated to the existing 2DPCA, and the called incremental 2DPCA (I2DPCA) is firstly presented to incrementally compute the principal components of a sequence of samples directly on the 2D image matrices without estimating the covariance matrices.
Therefore, the I2DPCA can improve the feature extraction speed and reduce the required memory.
However, the variations between the column direction, generally neglected, are also useful for the high-accuracy object recognition.
Thus, another incremental sequential row-column 2DPCA algorithm (IRC2DPCA), based on the proposed I2DPCA algorithm, is also proposed.
The IRC2DPCA can compress the image matrices in the row and column direction, and the feature matrices extracted by the IRC2DPCA are with less dimensions than the I2DPCA.
The substantial experimental results show that the IRC2DPCA, compared with the other three algorithms, can improve the convergence rates and the recognition rates, compress the dimensions of the feature matrices, and reduce the feature extraction time and the classification time.
American Psychological Association (APA)
Ge, Weimin& Sun, Mingyue& Wang, Xiaofeng. 2018. An Incremental Two-Dimensional Principal Component Analysis for Object Recognition. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1206799
Modern Language Association (MLA)
Ge, Weimin…[et al.]. An Incremental Two-Dimensional Principal Component Analysis for Object Recognition. Mathematical Problems in Engineering No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1206799
American Medical Association (AMA)
Ge, Weimin& Sun, Mingyue& Wang, Xiaofeng. An Incremental Two-Dimensional Principal Component Analysis for Object Recognition. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1206799
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206799