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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.
This paper proposes a new method to automatically detect important objects from video content. Our approach extracts video frames that show important objects, by recognition of typical TV production techniques. We also present a prototype application for DVRs, which utilizes the proposed method to enable easy access to important scenes of TV programs.
In this paper we introduce and exploit the concept of contextual rules in the field of object detection. These rules are defined as associations between different object likelihood maps and are learned from given examples. The contextual rules can be used to prime regions where a target object category occurs in an image given areas of other object categories. The principal idea is to locate several...
In this paper, we present a football event detection method by using multiple feature extraction and fusion. Instead of using low-level features, the proposed method is built upon visual, auditory features, text and audio keywords. Promising event detection results have been achieved. By using the proposed method, we have been able to detect the football events accurately. Experimental results have...
This paper presents a new neural network to perform the visual pattern classification task. The neural network is called I-PyraNet which is a hybrid implementation of the PyraNet and the concepts of the inhibitory fields. In order to improve the results obtained by this neural network, it is also presented the 2-D Gabor filter. Furthermore, both, the neural network and the filter, are applied over...
We describe a method for filtering object category from a large number of noisy images. This problem is particularly difficult due to the greater variation within object categories and only a few labeled object images available. Our method deals with it by using visual consistency and semi-supervised approach. The images of one category often share some visual consistency so that the most irrelevant...
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