|
Web
Education
Viewing 1-10 of 10 total results
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.
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 ...
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.
Independent component analysis: recent advances ...
Independent component analysis (ICA; Jutten & Hérault ) has been established as a fundamental way of analysing such multi-variate data. It learns a linear decomposition (transform) of the data, such as the more classical methods of factor analysis and principal component analysis (PCA).
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 ......
US7254257B2 - Method and apparatus of recognizing face ...
A method and apparatus for recognizing and searching for a face using 2nd-order independent component analysis (ICA) are provided. The method for describing feature points uses 2nd-order ICA d to describe a facial image space and improve recognition performance in various illumination conditions. According to the method and apparatus, use of pose or illumination invariant face descriptor ......
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....
IET Digital Library: Efficient eye detection method based ...
Detection of facial features such as eye, nose and mouth in the human face images is important for many applications like face identification or recognition systems. Independent components analysis (ICA) is an unsupervised learning method which decorrelates the higher-order statistics in addition to the second-order moments. Recently, it is used as a technique for face recognition....
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).
|
