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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....
 Subspace Based Object Recognition Using Support Vector ...
analysis of independent component analysis and principal component analysis (PCA) is also given for each experiment. 1-INTRODUCTION Object recognition, which is an easy task for a human observer, has long been the focus of much research in Computer Vision, forming an essential component of many machine-based object recognition systems. A large ......
Published Papers - University of Sheffield
Journal Publications. Stone JV, "Independent Component Analysis", The Encyclopedia of Statistics in Behavioral Science, BS Everitt and DC Howell (Eds), Wiley StatsRef: Statistics Reference Online, 2015. Download pdf file. Stone JV, "Using Reaction Times and Binary Responses to Estimate Psychophysical Performance: An Information-Theoretic Analysis", Frontiers in Decision Neuroscience, 8(35 ......
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).
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
CiteSeerX — Multilinear Independent Components Analysis
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the different factors, or modes, inherent to image formation, including scene structure, illumination, and imaging.
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....
Recognizing Action Units for Facial Expression Analysis
optical flow, principal component analysis, independent component analysis, local feature analysis, and Gabor wavelet representation. Best performances were obtained by Gabor wavelet representation and independent component analysis which achieved a 95% average recognition rate for 6 upper face AUs and 6 lower face AUs....
Eigenfaces: Recovering Humans from Ghosts | by Nev Acar ...
Eigenfaces is a method that is useful for face recognition and detection by determining the variance of faces in a collection of face images and use those variances to encode and decode a face in a machine learning way without the full information reducing computation and space complexity.
Learning Robust and Discriminative Manifold ...
for face and object recognition task. The second contribution of this thesis is a biologically motivated manifold learn-ing framework for image set classification by independent component analysis (ICA) for Grassmann manifolds. It has been discovered that the simple cells in the visual cortex learn spatially localized image representations....
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