顔認識 Archives — MATLAB Number ONE

Regularized Robust Coding for Face Recogntion

global MATLAB — Tue, 08 May 2018 05:25:07 +0000

This paper presented a novel robust regularized coding (RRC) model and an associated effective iteratively reweighted regularized robust coding (IR3 C) algorithm for robust face recognition (FR). One important advantage of RRC is its robustness to various types of outliers (e.g., occlusion, corruption, expression, etc.) by seeking for an approximate MAP (maximum a posterior estimation) solution of the coding […]

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Robust Kernel Representation with Statistical Local Features for Face Recognition

global MATLAB — Tue, 08 May 2018 05:12:19 +0000

In this project , we proposed a statistical local feature based robust kernel representation (SLF-RKR) model for face recognition. A robust representation model to image outliers (e.g., occlusion and real disguise) was built in the kernel space, and a multi-partition max pooling technology was proposed to enhance the invariance of local pattern feature to image misalignment and pose […]

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Metaface learning for sparse representation based face recognition

global MATLAB — Thu, 19 Apr 2018 07:38:47 +0000

Automatic face recognition (FR) has been, and remains being, one of the most visible and challenging research topics in computer vision, machine learning and biometrics. Although the facial images have a high dimensionality, they usually lie on a lower dimensional subspaces or submanifolds. Therefore, subspace learning and manifold learning methods have been dominantly and successfully used in appearance based FR , which […]

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Monogenic Binary Coding: An efficient Local Feature Extraction Approach to Face Recognition

global MATLAB — Thu, 19 Apr 2018 07:32:05 +0000

We proposed a novel face representation model, namely monogenic binary coding (MBC), based on the monogenic signal representation. One of the best merits of MBC is that it has much less time and space complexity than the widely used Gabor transformation based local feature extraction method. Through multi-scale monogenic signal representation, three kinds of features (e.g., local amplitude, […]

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On the Dimensionality Reduction for Sparse Representation based Face Recognition

global MATLAB — Mon, 16 Apr 2018 03:59:10 +0000

In this project, we discussed the dimensionality reduction (DR) of face images when using sparse representation based classifier (SRC) for classification. Our experiments on Extended Yale B, AR and ORL face databases demonstrated that the proposed DR algorithm has better performance than Eigenfaces and Randomfaces. It can achieve higher recognition rate under the same dimensionality […]

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gabor feature based sparse representation for face recognition with gabor occlusion dictionary

global MATLAB — Sun, 15 Apr 2018 12:55:37 +0000

In this paper, we proposed a Gabor-feature based SRC (GSRC) scheme, which uses the image local Gabor features for SRC, and proposed an associated Gabor occlusion dictionary computing algorithm to handle the occluded face images. Apart from the improved face recognition rate, one important advantage of GSRC is its compact occlusion dictionary, which has much less atoms than that […]

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