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Statistical methods of shape and appearance are powerful tools used in computer vision for near-correct interpretation of images. In this paper, we present a method for classifying facial expressions based on the extracted features of facial components. The face, the window to the inner self of an individual can be analyzed for outright expressions like sadness, happiness, anger, surprise, disgust...
This paper proposes a simple but powerful method for automatic classification of facial expressions from static images. Still images do not bare as much information as in video sequences which have much information/activities during the expression actions. The main aim here is to be able to classify every facial image into the six universally researched and accepted prototypic facial expressions like...
There has been steady effort to modelize or recognize human action in fields of computer visions or mechanical learning, which should lead to fruitful results. This study presents how to extract key postures that can explain human actions within video sequence. To detect key postures that can differentiate human actions significantly, we select key posture candidates using information entropy which...
In recent days, damages to information systems and network due to worm and virus using vulnerabilities of windows security have been rapidly increasing. How to deal with the attack using vulnerabilities of windows program is to install patch appropriately and rapidly. This study suggests security patch auto-management system which installs security patch file automatically to clients through automatic...
In this paper, we present a text segmentation method using wavelet packet analysis and k-means clustering algorithm. This approach assumes that the text and non-text regions are considered as two different texture regions. The text segmentation is achieved by using wavelet packet analysis as a feature analysis. The wavelet packet analysis is a method of wavelet decomposition that offers a richer range...
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