On nonlinear dimensionality reduction for face recognition
نویسندگان
چکیده
منابع مشابه
On nonlinear dimensionality reduction for face recognition
The curse of dimensionality has prompted intensive research in effective methods of mapping high dimensional data. Dimensionality reduction and subspace learning have been studied extensively and widely applied to feature extraction and pattern representation in image and vision applications. Although PCA has long been regarded as a simple, efficient linear subspace technique, many nonlinear me...
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A Face Recognition System is used to automatically identify or verify a person from digital image. Since capturing of face image is not very difficult process and does not require too much cooperation of the subject, it keeps the interest of researchers alive. In this paper, combination of linear and combination of nonlinear dimensionality reduction techniques are implemented separately for fac...
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The self-organizing map (SOM) is a classical neural network method for dimensionality reduction and data visualization. Visualization induced SOM (ViSOM) and growing ViSOM (gViSOM) are two recently proposed variants for a more faithful, metric-based and direct data representation. They learn local quantitative distances of data by regularizing the inter-neuron contraction force while capturing ...
متن کاملJoint discriminative dimensionality reduction and dictionary learning for face recognition
In linear representation based face recognition (FR), it is expected that a discriminative dictionary can be learned from the training samples so that the query sample can be better represented for classification. On the other hand, dimensionality reduction is also an important issue for FR. It can not only reduce significantly the storage space of face images, but also enhance the discriminati...
متن کاملDimensionality Reduction using SOM based Technique for Face Recognition
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms namely Principal Component Analysis (PCA), Self Organizing Maps (SOM), and Independent Component Analysis (ICA) have widely and successfully been used for face recognition. In this paper a SOM based technique for dimensio...
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ژورنال
عنوان ژورنال: Image and Vision Computing
سال: 2012
ISSN: 0262-8856
DOI: 10.1016/j.imavis.2012.03.004