Mesh Networks (WMNs) is a promising network access technology. As WMNs' applications become more and more popular, the number of users grows quickly and the quality of service needs to be improved. When we try to ...
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Supervisory control reconfiguration has been paid more attention due to its capacity of handling the uncertainties including resource failures, capability degradation, and task changes in discrete event systems. Howev...
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The advantage of on-line boosting is taking object tracking problem as a classification problem. Appropriate object feature are selected based on real time changes in the object. However, this method has a major drawb...
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The advantage of on-line boosting is taking object tracking problem as a classification problem. Appropriate object feature are selected based on real time changes in the object. However, this method has a major drawback. Due to the presence of occlusion situation, every transformation of object features may introduce a small number of error features. If it tracks the object for a long time, the accumulation of error features will cause the tracking object with position drift. The experimental analysis finds that in on-line boosting method, the global delivery of selector weight leads to the drift, while the actual object occlusion only affects a local area, but not the entire region. For this situation, this paper proposes the combination of on-line boosting and blocking to solve this problem. Its selector weights only change in the block, not in the global area, so it avoids errors in the global accumulation and the generation of drift. The proposed method by tracking a variety of object video sequences shows that even for severe occlusion cases, it also has strong robustness as well as real-time ability, namely tracking more than 10 objects.
Human behavior recognition has important applications in video surveillance and human-computer interaction, and it is also an important and challenging issue. Behavior recognition using depth information becomes a hot...
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Human behavior recognition has important applications in video surveillance and human-computer interaction, and it is also an important and challenging issue. Behavior recognition using depth information becomes a hot and popular spot. So far, human action recognition based on depth information has made some achievements, but it still does not have robust descriptors, and their accuracies are still not satisfactory. To solve above problems, this paper proposes three robust action descriptors for depth information, and then SVM classifier is adopted. Experiments on two public and challenging behavior recognition datasets show that our descriptors have strong robustness, distinction and stability, whose performance is much better than that of the state of the art algorithms.
Cloud computing is a recently developed new technology for complex systems with massive service sharing, which is different from the resource sharing of the grid computingsystems. In a cloud environment, service requ...
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Optimal stopping theory is developed to achieve a good trade-off between decision performance and decision efforts such as the consumed decision time. In this paper, the optimal stopping theory is applied to fast mode...
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In homogeneous or heterogeneous databases, the main direction of research on XML-based information interaction between databases is taking XML as middleware to realize the information exchange between data in the envi...
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Considering characteristic of mHealth communication and problems of existing methods, this paper presents a real-time communication method for mHealth based on extended XMPP protocol. The method can maintain the role ...
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Considering characteristic of mHealth communication and problems of existing methods, this paper presents a real-time communication method for mHealth based on extended XMPP protocol. The method can maintain the role status efficiently and reduce data latency during the communication process. Meanwhile, it can be extended flexibly to meet increasing communication demands of mHealth services. Furthermore, a system framework is presented to support telemonitoring scene. Finally, system implementation and feasibility tests verify the effectiveness of the method and framework.
As the semiconductor industry advances to nano-technology points, Network on Chip (NoC) components are becoming vulnerable to errors during the system operation. Consequently, fault-tolerant techniques for NoC are nee...
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Rising global energy demand, increasing electricity prices, and the limitation of natural resources have led to increased interest in energy monitoring of residential buildings. Much research has been done to examine ...
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