An improvement of energy-transfer features using DCT for face detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092994" target="_blank" >RIV/61989100:27240/14:86092994 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-07998-1_59" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-07998-1_59</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-07998-1_59" target="_blank" >10.1007/978-3-319-07998-1_59</a>

Result language
angličtina
Original language name
An improvement of energy-transfer features using DCT for face detection
Original language description
The basic idea behind the energy-transfer features (ETF) is that the appearance of objects can be successfully described using the function of energy distribution in the image. This function has to be reduced into a reasonable number of values. These values are then considered as the vector that is used as an input for the SVM classifier. The process of reducing can be simply solved by sampling; the input image is divided into the regular cells and inside each cell, the mean of the values is calculated.In this paper, we propose an improvement of this process; the Discrete Cosine Transform (DCT) coefficients are calculated inside the cells (instead of the mean values) to construct the feature vector. In addition, the DCT coefficients are reduced usingthe Principal Component Analysis (PCA) to create the feature vector with a relatively small dimensionally. The results show that using this approach, the objects can be efficiently encoded with the relatively small set of numbers with pro
Czech name
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Czech description
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Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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