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RFID and Face Recognition Based Security and Access ...
The researcher expect to increase strength of security by 50%. Face recognition under constrained condition and RFID are contactless processes. The approach presented in this paper for face recognition uses DWT and Euclidean distance method. Face recognition is a very important component in many applications like search engine and emotion detector....
 Recognizing Facial Actions by Combining Geometric Features ...
Gabor wavelet representation and independent component analysis. All of these systems [1, 7, 11] used a manual step to align the input images with a standard face image using the center of the eyes and mouth. In our previous system [21], multi-state face and facial component models are proposed for tracking and...
Face Modeling by Information Maximization
[42] C. Liu and H. Wechsler. Comparative assessment of independent component analysis (ica) for face recognition. In International conference on audio and video based biometric person authentication, 1999. [43] Q. Liu, J. Cheng, H. Lu, and S. Ma. Modeling face appearance with nonlinear independent component analysis....
A Robust Method for Nose Detection under Various ...
It depends on the local appearance and shape of nose region characterized by edge information. Independent Components Analysis (ICA) is used to learn the appearance of nose. We show experimentally that using edge information for characterizing appearance and shape outperforms using intensity information....
icalab ICA : Independent component analysis, based - CodeBus
icalab ICA : Independent component analysis, based on MATLAB. FastICA_2.4] - based on independent component analysis [independentcomponentanalysis(maltabcode)used] - independent component analysis (maltab c[] - fast algorithm, the test after test, we[Classification-MatLab-Toolbox] - pattern recognition Matlab toolbox, incl[] - ICA achieving Matlab feature extraction...
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 ......
CiteSeerX — Citation Query Independent component analysis ...
New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. ... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into ......
Independent component analysis: an introduction: Trends in ...
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. This article illustrates these applications, and provides ...
US20080247608A1 - Method, System, Storage Medium, and Data ...
US20080247608A1 US11/571,341 US57134105A US2008247608A1 US 20080247608 A1 US20080247608 A1 US 20080247608A1 US 57134105 A US57134105 A US 57134105A US 2008247608 A1 US2008247608 A
Enhancing face recognition using Directional Filter Banks ...
Linear Discriminant Analysis (LDA) PCA constructs the face space without using face class (cate- ry) information where training considers the whole face data. owever, in LDA the goal is to find an efficient way to represent e face vector space [19,3] by exploiting the class information hich can be helpful for the identification task....
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