A Joint Learning Approach to Face Detection in Wavelet Compressed Domain
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-11
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Face detection has been an important and active research topic in computer vision and image processing.
In recent years, learning-based face detection algorithms have prevailed with successful applications.
In this paper, we propose a new face detection algorithm that works directly in wavelet compressed domain.
In order to simplify the processes of image decompression and feature extraction, we modify the AdaBoost learning algorithm to select a set of complimentary joint-coefficient classifiers and integrate them to achieve optimal face detection.
Since the face detection on the wavelet compression domain is restricted by the limited discrimination power of the designated feature space, the proposed learning mechanism is developed to achieve the best discrimination from the restricted feature space.
The major contributions in the proposed AdaBoost face detection learning algorithm contain the feature space warping, joint feature representation, ID3-like plane quantization, and weak probabilistic classifier, which dramatically increase the discrimination power of the face classifier.
Experimental results on the CBCL benchmark and the MIT + CMU real image dataset show that the proposed algorithm can detect faces in the wavelet compressed domain accurately and efficiently.
American Psychological Association (APA)
Huang, Szu-Hao& Lai, Shang-Hong. 2014. A Joint Learning Approach to Face Detection in Wavelet Compressed Domain. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-480599
Modern Language Association (MLA)
Huang, Szu-Hao& Lai, Shang-Hong. A Joint Learning Approach to Face Detection in Wavelet Compressed Domain. Mathematical Problems in Engineering No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-480599
American Medical Association (AMA)
Huang, Szu-Hao& Lai, Shang-Hong. A Joint Learning Approach to Face Detection in Wavelet Compressed Domain. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-480599
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-480599