Fighting shots are the highlights of action movies and an effective approach to discriminating fighting shots is very useful for many applications, such as movie trailer construction, movie content filtering, and movi...
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Fighting shots are the highlights of action movies and an effective approach to discriminating fighting shots is very useful for many applications, such as movie trailer construction, movie content filtering, and movie content retrieval. In this paper, we present a novel method for this task. Our approach first extracts the reliable motion information of local invariant features through a robust keypoint tracking computation; then foreground keypoints are distinguished from background keypoints by a sophisticated voting process; further, the parameters of the camera motion model is computed based on the motion information of background keypoints, and this model is then used as a reference to compute the actual motion of foreground keypoints; finally, the corresponding feature vectors are extracted to characterizing the motions of foreground keypoints, and a support vector machine （SVM） classifier is trained based on the extracted feature vectors to discriminate fighting shots. Experimental results on representative action movies show our approach is very effective.
In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy e...
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In order to probe the secret of our brain, it is necessary to design large scale dynamical neural circuits( more than 106 neurons) to simulate complex process of our brain. But such kind task is not easy to achieve on...
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Vladimir N. Vapnik. (1998) pointed out that maxlikelihood functions in EM algorithms are just a special risk function. Based on this opinion, a novel EM algorithm uses a risk function differ with maxlikelihood functio...
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Contextual question answering （CQA）, in which user information needs are satisfied through an interactive question answering （QA） dialog, has recently attracted more research attention. One challenge is to fuse co...
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Contextual question answering （CQA）, in which user information needs are satisfied through an interactive question answering （QA） dialog, has recently attracted more research attention. One challenge is to fuse contextual information into the understanding process of relevant questions. In this paper, a discourse structure is proposed to maintain semantic information, and approaches for recognition of relevancy type and fusion of contextual information according to relevancy type are proposed. The system is evaluated on real contextual QA data. The results show that better performance is achieved than a baseline system and almost the same performance as when these contextual phenomena are resolved manually. A detailed evaluation analysis is presented.
People often feel the limitation of time to read the continuously increasing articles they need to read. It is a grand challenge to handle the explosion of articles. To understand how humans read articles and get the ...
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Word alignment is a fundamental step in machine translation. Current statistical machine translation systems suffer from a major drawback: they only extract rules from 1-best alignments, which adversely affects the ru...
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Take multi-time-phase Landstat TM/ETM+ Remote Sensing images (1990,2002,2007) of Nanning City as data source and use RS and GIS intergration technology to extract the informa-tion of city. The paper analyses the prope...
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