Open Access
Contourlet and Nearest Feature Line Based Feature Extraction Approach for One Prototype Sample Problem.
Jeng-Shyang Pan,Lijun Yan,Shu-Chuan Chu,John F. Roddick +3 more
- Vol. 7, pp 1052-1059
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The article was published on 2016-01-01 and is currently open access. It has received 0 citations till now. The article focuses on the topics: Feature (computer vision) & Feature extraction.read more
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Journal ArticleDOI
Face recognition from a single image per person: A survey
TL;DR: Categorize and evaluate face recognition algorithms that rely heavily on the size and representative of training set, and the prominent algorithms are described and critically analyzed.
Journal ArticleDOI
Face recognition using the nearest feature line method
Stan Z. Li,Juwei Lu +1 more
TL;DR: A novel classification method, called the nearest feature line (NFL), for face recognition, based on the nearest distance from the query feature point to each FL, which achieves the lowest error rate reported for the ORL face database.
Directional multiresolution image representations
TL;DR: This thesis focuses on the development of new "true" two-dimensional representations for images using a discrete framework that can lead to algorithmic implementations and a new family of block directional and orthonormal transforms based on the ridgelet idea.
Journal ArticleDOI
Rapid and brief communication: Two-dimensional discriminant transform for face recognition
TL;DR: 2DLDA provides a sequentially optimal image compression mechanism, making the discriminant information compact into the up-left corner of the image, and suggests a feature selection strategy to select the most discriminative features from the corner.
Journal ArticleDOI
Face recognition with one training image per person
Jianxin Wu,Zhi-Hua Zhou +1 more
TL;DR: In this paper, an extension of the eigenface technique, i.e. projection-combined principal component analysis, (PC)2A, is proposed and it requires less computational cost and achieves 3-5% higher accuracy on a gray-level frontal view face database where each person has only one training image.