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 3D Reconstruction and Face Recognition Using Kernel-Based ...
Keywords: Independent component analysis, 3D human face reconstruction, 3D human face recognition, back-propagation algorithm, neural networks. 1. Introduction When we use a camera to capture 3D objects, we lose the depth information of the 3D objects and only obtain the 2D image information. However, the depth information of the 3D objects ......
Action recognition based on overcomplete independent ...
Independent component analysis (ICA) , , a specific case of sparse coding when constraining the number of basis functions to equal the feature dimension, also shows similar response properties with simple cells in visual cortex and achieves success in face recognition and action recognition .
Face recognition using independent component analysis and ...
Independent component analysis (ICA) (Bell and Sejnowski, 1995) is also a relatively recent technique which has been mainly applied to blind signal separation, though it has been successfully applied to the face recognition problem too. ICA is a feature extraction technique, while SVM are a type of classifiers.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE ...
component analysis, independent component analysis, local feature analysis, and Gabor wavelet representation. The best performances were obtained by using Gabor wavelet representation and independent component analysis with which a 95.5 percent average recognition rate was reported for six single upper face AUs (AU 1, AU 2, AU 4, AU 5, AU 6,...
Independent Component Representations for Face Recognition
Keywords: Independent component analysis, ICA, principal component analysis, PCA, face recognition. 1. INTRODUCTION Several advances in face recognition such as "H~lons,~ " "Eigenfa~es,~ " and "Local Feature Analysis4" have employed forms of principal component analysis, which addresses only second-order moments of the input. Principal component...
Face Recognition Using Independent Component Analysis and ...
Support Vector Machines (SVM) and Independent Component Analysis (ICA) are two powerful and relatively recent techniques. SVMs are classifiers which have demonstrated high generalization capabilities...
Enhancing Performance of Face Recognition System Using ...
facebook uses face recognition system to help automate user tagging in photographs. To design high performance algorithms for automatic face recognition systems is a challenging task in the field of computer vision and pattern recognition for real time applications. Independent Component Analysis (ICA) is a...
Independent component analysis: an introduction ...
Independent component analysis (ICA) is a method for automatically identifying the underlying factors in a given data set. This rapidly evolving technique is currently finding applications in analysis of biomedical signals (e.g. ERP, EEG, fMRI, optical imaging), and in models of visual receptive fields and separation of speech signals.
Independent component analysis - Wikipedia
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that the subcomponents are non-Gaussian signals and that they are statistically independent from each other. ICA is a special case of blind source separation.A common example application is the "cocktail party problem ...
Region-Based Representations for Face Recognition
accurately recognize the stimuli. Given that this does not occur, we can infer that fine edge information is not a critical prerequisite for face recognition. Given the limitations of pixel and edge-based primitives, we propose the use of novel image mea-surements that implement a region-based representational strategy.
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