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.
Background subtraction is a technique for detecting moving objects in video frames. A simple BS process involves building a model of the background and extracting regions of the foreground (moving objects) with the assumptions that the camera remains stationary and there exist no movements in the background. Video object extraction is a critical task in multimedia analysis and editing. Normally, the...
Text Classification is an important field of research. There are a number of approaches to classify text documents. However, there is an important challenge to improve the computational efficiency and recall. In this paper, we propose a novel framework to segment Chinese words, generate word vectors, train the corpus and make prediction. Based on the text classification technology, we successfully...
Text Classification is an important field of research. There are a number of approaches to classify text documents. However, there is an important challenge to improve the computational efficiency and recall. In this paper, we propose a novel framework to segment Chinese words, generate word vectors, train the corpus and make prediction. Based on the text classification technology, we successfully...
In this paper, we solve the searching problem by high level features used by sign language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left sign and right sign in specific areas. By computing the signs' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the signs' dynamic features. Consequently, we segment...
In this paper, a novel approach based on acoustic cues for automatic segmenting television stream into individual programs is proposed. This presented method is composed of the following steps: Several sets of repetitions in the audio track is detected by using silence detection and robust audio hashing; The found repetitions are treated as advertisements if the range of their length is from 5 seconds...
This paper presents a system called DCMR. Content-based video searching is a challenging field, and most research focus on the low level features such as color histogram, texture and etc. In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right...
In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands' dynamic features. Consequently, we segment...
This paper presents a system called DCMR. Content-based video searching is a challenging field, and most research focus on the low level features such as color histogram, texture and etc. In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right...
In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands' dynamic features. Consequently, we segment...
We present a revised method to compute the similarity of traditional string edit distance in this paper. Because this method lacks some types of normalization, it would bring some computation errors when the sizes of the strings that are compared are variable. In order to compute the edit distance, a new algorithm is introduced. In this paper, we solve the retrieval problem by high level features...
In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands' dynamic features. Consequently, we segment...
Text Classification is an important field of research. There are a number of approaches to classify text documents. However, there is an important challenge to improve the computational efficiency and recall. In this paper, we propose a novel framework to segment Chinese words, generate word vectors, train the corpus and make prediction. Based on the text classification technology, we successfully...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.