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This article shows the improvement of automatic cartoon classification. Two new visual features - color component and color kind based on region segmentation - are proposed. Compared to traditional HSV color histogram and texture, experiment using the two new features can achieve better result, with less dimensions and higher mining efficiency.
News reports in TV provide important and timely information about the city and the world to citizens. Moreover, data mining and indexing of news video clips provide a good source of information. However, news video usually consists of more than one news story. One must split them into individual news before indexing. Owing to the nature of news reports, the news anchorperson usually appears in the...
Detection of the commercials in TV videos is hard because the diversity of them puts up a rather high barrier to find an appropriate model. After some studies of existing commercial detection works, we try to deal with this problem through a robust TV commercial detection approach. Firstly a sets of basic features that facilitate distinguishing commercial from general program are analyzed. Then, the...
A novel classification method of video shot genre based on data-mining has been proposed. Shot boundary detection and key frames extraction are firstly performed. Then, some visual features such as color and motion are extracted for the key frame and shots. Furthermore, decision tree is applied to discover the rules between these features and shots genres from numerous training data. These rules are...
In this paper we have designed a neural network based movie genres classifier. The Movie classifier characterizes the movie clips into different movie genres. The characterization is based on low level audio-visual features. We have extracted the computable audio-visual features from the movie clips which are inspired by the techniques and film grammars used by many filmmakers to endow specific characteristics...
In this paper, we propose a new method based on wavelet transform, statistical features and central moments for both graphics and scene text detection in video images. The method uses wavelet single level decomposition LH, HL and HH subbands for computing features and the computed features are fed to k means clustering to classify the text pixel from the background of the image. The average of wavelet...
Wireless Capsule Endoscopy (WCE) is a non invasive procedure which is used to view the lower gastrointestinal tract. Physicians can detect diseases such as bleeding, Crohn's disease, peptic ulcers, and colon cancer. In this paper a methodology is presented to identify peptic ulcers in the small intestine automatically. It first performs color transformation into the HSV color space; it utilizes log...
SVM is one of the state-of-the-art techniques for image and video classification. When multiple kernels are available, the recently introduced multiple kernel SVM (MK-SVM) learns an optimal linear combination of the kernels, providing a new method for information fusion. In this paper we study how the behaviour of MK-SVM is affected by the norm used to regularise the kernel weights to be learnt. Through...
With popularization of multimedia devices, semantic analysis of sports video has been widely studied. In this paper, we propose a highlight generation method for basketball games. To create a video highlight, the proposed method selects interesting shots by modeling excitements of the game using score information. For this purpose, a video is first segmented into shots and classified as play and nonplay...
Recognition of signs in sentences requires a training set constructed out of signs found in continuous sentences. Currently, this is done manually, which is a tedious process. In this work, we consider a framework where the modeler just provides multiple video sequences of sign language sentences, constructed to contain the vocabulary of interest. We learn the models of the recurring signs, automatically...
In this paper, we present a new method for classifying shot type in sports video based on visual attention. The problem is important for applications such as video structure analysis and content understanding. In particular, two-stage off-line learning processes perform knowledge extraction of semantic concepts and automatic shot classification, respectively. In the first stage, the extracted prominent...
Interpretation of WCE video is nowadays largely left to the visual inspection of a medical specialist. This tedious and time consuming task could greatly benefit from techniques that automatically classify and exclude from further processing the non-relevant frames in the video. To this aim in this paper the construction of an indicator function that takes high value, whenever there is a sudden change,...
Our paper presents a new approach for the recognition of highlights in soccer video. Our contribution consists of the combination of Bayesian theorem inferences and Hidden Markov Models (HMMs). We build HMMs to calculate probabilities that a test video segment belongs to highlight and non highlight classes. Then, we apply the Bayesian theorem on the two previous probabilities. Our system has achieved...
In this paper, we propose a novel hierarchical framework for soccer (football) video classification. Unlike most existing video classification approaches, which focus on shot detection followed by classification based on clustering using shot aggregation, the proposed scheme perform a top-down video scene classification which avoids shot clustering. This improves the classification accuracy and also...
With the fast development of video semantic analysis, there has been increasing attention to the typical issue of the semantic analysis of soccer program. Based on the color feature analysis, this paper focuses on the video shot segmentation problem from the perspective of semantic analysis, i.e. the semantic shot segmentation. Most existing works segment and classify the shot by using the dominant...
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