Now with a large lexicon of over 300 semantic concepts available for indexing purpose, video retrieval can be made easier by leveraging on the available semantic indices. However, any successful concept-based video re...
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ISBN:
(纸本)9781605580708
Now with a large lexicon of over 300 semantic concepts available for indexing purpose, video retrieval can be made easier by leveraging on the available semantic indices. However, any successful concept-based video retrieval approach must take the following into account: though improving continuously, these concept indexing results are still far from perfect;more concepts are awaiting for detection instead of being detected due to the limited amount of annotated data. If possible, a structured query formulation other than a simple AND logic of some chosen concepts is more desirable to model the complex query need with the fixed concept lexicon. In this paper, we propose a conceptbased interactive video retrieval approach to tackle these problems. To better represent the query information need, the proposed approach learns through the feedback information a structured formulation which consists of multiple semantic concept combination terms. Instead of taking the top-ranked items from the selected concepts, it leverages on a simple mining algorithm to drill down to concept-segments where the positive examples are most densely populated than the negative examples. We evaluate the proposed method on the large scale TRECVid 05&06 data sets, and achieve promising results. Retrieval in concept-segment level has a 14% improvement upon the concept-level. Structured query formulation improves around 13% compared with the simple logical AND formulation. The learning and retrieval process only takes 300ms, satisfying the real-time interactive search need. Copyright 2008 ACM.
We proposed a fully-software distributed failure diagnosis system for vehicles based on the TH-OSEK realtime embedded OS platform we previously developed. The diagnosis system puts all the ECUs into a virtual logical ...
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In some real-world classification tasks, the classifier may be trained on a data set which does not reflect the class distribution of the real data set. Such sampling bias or virtual concept drift may seriously affect...
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In some real-world classification tasks, the classifier may be trained on a data set which does not reflect the class distribution of the real data set. Such sampling bias or virtual concept drift may seriously affect the classification accuracy. Previous researches on this topic mainly concern classifiers with explicit a posteriori probabilities output. There has been a framework to adjust the original classifier using Expectation Maximization (EM) algorithm for such classifiers. The margin based classifier Support Vector Machine (SVM), has not been studied under this framework because of the lack of probabilistic output. In this paper, we discuss the probabilistic output of SVM and propose a Gaussian Mixture Model (GMM) to approximate the class conditional distribution of the margin so as to adjust the classifier using the EM framework. Experimental results on standard machine learning data sets show that the proposed algorithm can improve the classification accuracy on most of these problems. It performs especially well on those data sets with low classification accuracy.
Autonomous landing is an important part of the autonomous control of Unmanned Aerial Vehicles (UAVs). In this article we present the design and implementation of a vision algorithm for autonomous landing. We use an on...
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In the paper, an interactive video retrieval system with rich features and friendly interface is presented briefly. The goal is to help users to find what they want with some analysis and visualization tools provided ...
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ISBN:
(纸本)9781605580708
In the paper, an interactive video retrieval system with rich features and friendly interface is presented briefly. The goal is to help users to find what they want with some analysis and visualization tools provided by the system. It searches shots in text, image and concept space respectively and fuses these scores finally. Friendly interface is designed to help users to browse and label the result conveniently. With such an interface, user and system can exchange information effectively and efficiently in the retrieval procedure.
The maximum mutual information (MaxMI) criterion is used as the adaptation cost for the adaptive filtering. This criterion is robust to measure distortions, and has strong connection with traditional mean-square error...
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Semantic concept learning is one of the most challenging problems in video retrieval. The key barrier for semantic concept learning is lack of annotated training data. Internet videos are different from ordinary video...
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Opinion leaders play a very important role in information diffusion;they are found in all fields of society and influence the opinions of the masses in their fields. Most proposed algorithms on identifying opinion lea...
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A new background subtraction algorithm based on a combination of texture, color and intensity information is presented. The texture is depicted by DLBP, a modified version of LBP, color is a local template in HS color...
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News topics, which are constructed from news stories using the techniques of Topic Detection and Tracking (TDT), bring convenience to users who intend to see what is going on through the Internet. However, it is almos...
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ISBN:
(纸本)9781595939913
News topics, which are constructed from news stories using the techniques of Topic Detection and Tracking (TDT), bring convenience to users who intend to see what is going on through the Internet. However, it is almost impossible to view all the generated topics, because of the large amount. So it will be helpful if all topics are ranked and the top ones, which are both timely and important, can be viewed with high priority. Generally, topic ranking is determined by two primary factors. One is how frequently and recently a topic is reported by the media;the other is how much attention users pay to it. Both media focus and user attention varies as time goes on, so the effect of time on topic ranking has already been included. However, inconsistency exists between both factors. In this paper, an automatic online news topic ranking algorithm is proposed based on inconsistency analysis between media focus and user attention. News stories are organized into topics, which are ranked in terms of both media focus and user attention. Experiments performed on practical Web datasets show that the topic ranking result reflects the influence of time, the media and users. The main contributions of this paper are as follows. First, we present the quantitative measure of the inconsistency between media focus and user attention, which provides a basis for topic ranking and an experimental evidence to show that there is a gap between what the media provide and what users view. Second, to the best of our knowledge, it is the first attempt to synthesize the two factors into one algorithm for automatic online topic ranking. Copyright 2008 by ACM.
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