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Wyświetlanie 1-3 z 3
Tytuł:
Automatic perception of significant image features based on psychology of vision
Autorzy:
Lisowska, A.
Kotarski, W.
Powiązania:
https://bibliotekanauki.pl/articles/333672.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
wewnętrzna wymiarowość
automatic perception
intrinsic dimensionality
Opis:
Recent investigations in neuropsychology and psychology of vision have proven that human eye does not get all the information from the surrounding world in the same degree. There are three classes of signals received by human brain. The more important one is the information about features such as corners, junctions, ends of lines, etc. Straight lines and edges are the second in the hierarchy of importance. And the last ones are textures they support the less important information about objects. Basing on these results, in image processing, theory of intrinsic dimensionality and related to it theory of feature extractors have been established. In the paper a survey of approaches that are used for construction of feature extractors based on intrinsic dimensionality have been presented. To carry out experiments the approach based on geometrical wavelets has been chosen and the software prepared by the first author has been used. Experiments presented in the paper have been performed on relatively complex images that had been faces' images. They confirmed that the information about the basic elements of faces (eyes, nose, lips, etc.) might be properly extracted from the face with the usage of the feature extractor. Moreover, the experiments have shown that in this way one could obtain the smallest possible amount of information, which was enough that human eyes yet have seen the face. Very promising results of experiments suggest that it is possible to use the proposed approach to face identification and recognition. Also some possible medical applications have been suggested.
Źródło:
Journal of Medical Informatics & Technologies; 2004, 7; MIP31-40
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Semi-automatic human emotions recognition method based on I2D features
Autorzy:
Lisowska, A.
Kotarski, W.
Kownacki, A.
Powiązania:
https://bibliotekanauki.pl/articles/333730.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
podstawowe emocje
rozpoznanie
wewnętrzna wymiarowość
falki geometryczne
basic emotions
recognition
intrinsic dimensionality
geometrical wavelets
Opis:
In the paper we present quite new approach to the problem of human emotion recognition with use of face images. We assume that basic emotions such as anger, disgust, fear, happiness, sadness, surprise are expressed by face mimic. Face images with the well defined emotions may be performed using the method based on geometrical wavelets (beamlets) in order to extract intrinsically two dimensional features, the most important ones from the Human Visual System point of view. Such an approach can be successfully applied in extraction process of the most important features that are responsible for recognition of basic elements of face (eyes, nose, lips, etc.). The listed elements of face have a little different location that depends on emotion expressed. It has been proved experimentally that it is possible using very small amount of information extracted from a face image, by the so-called beamlet extractor, to recognize emotion with high accuracy. Very promising results of experiments suggest that the method should be further investigated and improved.
Źródło:
Journal of Medical Informatics & Technologies; 2005, 9; 215-222
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of the maximum likelihood estimator for determining the intrinsic dimensionality of high-dimensional data
Autorzy:
Karbauskaitė, R.
Dzemyda, G.
Powiązania:
https://bibliotekanauki.pl/articles/331342.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
multidimensional data
intrinsic dimensionality
maximum likelihood estimator
manifold learning method
image understanding
dane wielowymiarowe
wymiarowość wewnętrzna
prawdopodobieństwo maksymalne
rozpoznawanie obrazu
Opis:
One of the problems in the analysis of the set of images of a moving object is to evaluate the degree of freedom of motion and the angle of rotation. Here the intrinsic dimensionality of multidimensional data, characterizing the set of images, can be used. Usually, the image may be represented by a high-dimensional point whose dimensionality depends on the number of pixels in the image. The knowledge of the intrinsic dimensionality of a data set is very useful information in exploratory data analysis, because it is possible to reduce the dimensionality of the data without losing much information. In this paper, the maximum likelihood estimator (MLE) of the intrinsic dimensionality is explored experimentally. In contrast to the previous works, the radius of a hypersphere, which covers neighbours of the analysed points, is fixed instead of the number of the nearest neighbours in the MLE. A way of choosing the radius in this method is proposed. We explore which metric—Euclidean or geodesic—must be evaluated in the MLE algorithm in order to get the true estimate of the intrinsic dimensionality. The MLE method is examined using a number of artificial and real (images) data sets.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 895-913
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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