Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
In this paper we approach the problem of scene recognition in paintings. We tackle this task with the aid of Convolutional Neural Networks and a large database consisting of around 80,000 paintings. The main purpose is to identify an efficient method to enlarge the database by domain transfer from photographic content to artistic content. Thus, we discuss the practical capabilities of a recent method...
To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images,...
This papers presents the use of color imaging as a starting point of burn wound evaluation, by the discrimination between healthy skin and burn wound. The skin/burn area identification is performed pixel-wise, according to the properties of an entire encompassing patch. The classification is learned under a supervised scenario, according to a ground truth defined by specialist surgeons from a large...
This paper addresses the problem of recognizing illogical object juxtaposing in the specific form of classifying digitized paintings in art movements. More precisely we distinguish between realism and surrealism movements. We propose a system based on feature extraction and machine learning that is able to understand the scene in the digitized paintings and to classify the art works from the two movements...
In this paper we concentrate our efforts on the analysis of the facial landmarks dynamics as being a relevant method to access the subject's emotion. Given the person's facial landmarks we describe their trajectory with respect to the neutral pose and out of this trajectory we extract relevant features that are subsequently entered into a classification system for the actual recognition of emotion...
In this paper we describe a new system for eye center (pupil) localization. The patch centered on the eye is described by concatenations of integral and edge projections. Next, for dimensionality reduction, the Principal Component Analysis (PCA) technique is employed, while the discrimination among possible candidates is performed with a Bagged ensemble of Regression Trees (BRT) classifier. The accuracy...
In this paper a method for localization of the mouth area followed by subsequent analysis of the expression is proposed. First we identify the area of interest using a face detection solution complemented with a refined search based on integral projections. The precise lower face expression is determined in a framework where the power of discrimination of bank of low — pass and band — pass filters...
Automatic detection of human face features plays a significant role in expression recognition and human computer interaction. Human eyebrows shape has good specificity and stability, hence precise localization outlines a series of threads for face expression analysis. This paper will introduce a simple method for eyebrow localization. The determined positions allow geometrical extraction of the upper...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.