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Face Recognition by Independent Component | Request PDF
Face Recognition by Independent Component. ... components of natural scenes are localized and oriented edge lters similar to Gabor lters. ... and independent component analysis (ICA) for face ...
 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 ...
Principal Component Analysis is used for the Face Recognition System [13]. This research used a version of PCA for facial images in FERET database where input picture is treated as random ...
Face Recognition Using Independent Component Analysis and ...
Déniz⋆⋆ O., Castrillón M., Hernández M. (2001) Face Recognition Using Independent Component Analysis and Support Vector Machines ⋆. In: Bigun J., Smeraldi F. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2001. Lecture Notes in Computer Science, vol 2091.
Independent components analysis-based nose detection method
The method adopt Independent Components Analysis (ICA) as a subspace classifier to classify the face candidate region to nose or non nose. The ICA basis vectors are estimated by the FastICA algorithm. The training has been done using features of nose appearance and shape characterized by the edge information.
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 .
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.
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 ......
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 ...
Independent Component Analysis: A Review
analysis, projection pursuit and factor analysis. So Independent Component Analysis (ICA) is a method with help of which we can have a linear representation of nongaussian data so that the components are statistically independent. So, in this paper we see the basic theory and application of ICA. Key words: linear transformations makes ...
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