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Face recognition based on independent component analysis
In this paper, a novel method for independent component analysis (ICA) with 2-D Principle Component Analysis (2DPCA) in face recognition is presented, called 2DPCA-ICA.
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 - Cambridge Core
Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models.
 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 ...
Face Recognition Based on ICA Combined with FLD
Abstract. Recently in face recognition, as opposed to our expectation, the performance of an ICA (Independent Component Analysis) method combined with LDA (Linear Discriminant Analysis) was reported as lower than an ICA only based method.
Various Techniques used for Face Recognition
In this approach, complete face region is taken into account as input data into face catching system. One of the best example of holistic methods are Eigenfaces, PCA, Linear Discriminant Analysis and independent component analysis etc. Let's see the steps of Eigenfaces Method : This approach covers face recognition as a two-dimensional ......
Face Recognition for Beginners. Face Recognition is a ...
There are many statistical tools, which used for face recognition. These analytical tools used in a two or more groups or classification methods. These tools are as follows-4.2.1.Principal Component Analysis [PCA]:-One of the most used and cited statistical method is the Principal Component Analysis.
ICA for dummies – Arnaud Delorme
Independent Component Analysis is a signal processing method to separate independent sources linearly mixed in several sensors. For instance, when recording electroencephalograms (EEG) on the scalp, ICA can separate out artifacts embedded in the data (since they are usually independent of each other).
Sample gallery - Accord.NET Machine Learning in C#
Independent component analysis for blind source separation. Download the application; ... Learning and recognition of mouse gestures using hidden Markov model-based classifiers and Hidden Conditional Random Fields. ... Face detection using the Face detection based in Haar-like rectangular features method often known as the Viola-Jones method....
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