Polynomial features for robust face authentication
Conrad Sanderson,Kuldip K. Paliwal +1 more
- 24 Jun 2002
- Vol. 3, pp 997-1000
TL;DR: Results on the multi-session VidTIMIT database suggest that the proposed feature set is the most robust, followed by (in order of robustness and performance): 2D Gabor wavelets; 2D DCT coefficients; PCA (eigenface) derived features.
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Abstract: We introduce the DCT-mod2 facial feature extraction technique which utilizes polynomial coefficients derived from 2D DCT coefficients of spatially neighbouring blocks We evaluate its robustness and performance against three popular feature sets for use in an identity verification system subject to illumination changes Results on the multi-session VidTIMIT database suggest that the proposed feature set is the most robust, followed by (in order of robustness and performance): 2D Gabor wavelets; 2D DCT coefficients; PCA (eigenface) derived features Moreover, compared to Gabor wavelets, the DCT-mod2 feature set is over 80 times quicker to compute
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Citations
Face recognition in unconstrained videos with matched background similarity
Lior Wolf,Tal Hassner,Itay Maoz +2 more
- 20 Jun 2011
TL;DR: A comprehensive database of labeled videos of faces in challenging, uncontrolled conditions, the ‘YouTube Faces’ database, along with benchmark, pair-matching tests are presented and a novel set-to-set similarity measure, the Matched Background Similarity (MBGS), is described.
Partial Face Recognition: Alignment-Free Approach
TL;DR: It is argued that a probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors by adopting a variable-size description which represents each face with a set of keypoint descriptors.
Comparison of MLP and GMM classifiers for face verification on XM2VTS
TL;DR: Two classifier approaches, namely classifiers based on Multi Layer Perceptrons (MLPs) and Gaussian Mixture Models (GMMs), are compared for use in a face verification system and it is shown that for low resolution faces the MLP approach has slightly lower error rates than theGMM approach; however, the GMM approach easily outperforms theMLP approach for high resolution faces and is significantly more robust to imperfectly located faces.
Partial face recognition: An alignment free approach
Shengcai Liao,Anil K. Jain +1 more
TL;DR: An alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image, which is superior in recognizing both holistic and partial faces without requiring alignment.
Multimodal Cancelable Biometrics
Padma Polash Paul,Marina L. Gavrilova +1 more
- 24 Sep 2012
TL;DR: A new cancelable biometric template generation algorithm is developed using random projection and transformation-based feature extraction and selection and validated on multi-modal face and ear database.
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Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
Eigenfaces for Recognition
Matthew Turk,Alex Pentland +1 more
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