8,943 research outputs found

    Egocentric Hand Detection Via Dynamic Region Growing

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    Egocentric videos, which mainly record the activities carried out by the users of the wearable cameras, have drawn much research attentions in recent years. Due to its lengthy content, a large number of ego-related applications have been developed to abstract the captured videos. As the users are accustomed to interacting with the target objects using their own hands while their hands usually appear within their visual fields during the interaction, an egocentric hand detection step is involved in tasks like gesture recognition, action recognition and social interaction understanding. In this work, we propose a dynamic region growing approach for hand region detection in egocentric videos, by jointly considering hand-related motion and egocentric cues. We first determine seed regions that most likely belong to the hand, by analyzing the motion patterns across successive frames. The hand regions can then be located by extending from the seed regions, according to the scores computed for the adjacent superpixels. These scores are derived from four egocentric cues: contrast, location, position consistency and appearance continuity. We discuss how to apply the proposed method in real-life scenarios, where multiple hands irregularly appear and disappear from the videos. Experimental results on public datasets show that the proposed method achieves superior performance compared with the state-of-the-art methods, especially in complicated scenarios

    Communication Theoretic Data Analytics

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    Widespread use of the Internet and social networks invokes the generation of big data, which is proving to be useful in a number of applications. To deal with explosively growing amounts of data, data analytics has emerged as a critical technology related to computing, signal processing, and information networking. In this paper, a formalism is considered in which data is modeled as a generalized social network and communication theory and information theory are thereby extended to data analytics. First, the creation of an equalizer to optimize information transfer between two data variables is considered, and financial data is used to demonstrate the advantages. Then, an information coupling approach based on information geometry is applied for dimensionality reduction, with a pattern recognition example to illustrate the effectiveness. These initial trials suggest the potential of communication theoretic data analytics for a wide range of applications.Comment: Published in IEEE Journal on Selected Areas in Communications, Jan. 201

    Variation of the Fine-Structure Constant from the de Sitter Invariant Special Relativity

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    There are obvious discrepancies among various experimental constraints on the variation of the fine-structure constant, α\alpha. We attempt to discuss the issue in the framework of de Sitter invariant Special Relativity (SRc,R{\cal SR}_{c,R}) and to present a possible solution to the disagreement. In addition, on the basis of the observational data and the discussions presented in this Letter, we derive a rough theoretical estimate of the radius of the Universe.Comment: 8 pages, no figure

    The robustness of interdependent clustered networks

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    It was recently found that cascading failures can cause the abrupt breakdown of a system of interdependent networks. Using the percolation method developed for single clustered networks by Newman [Phys. Rev. Lett. {\bf 103}, 058701 (2009)], we develop an analytical method for studying how clustering within the networks of a system of interdependent networks affects the system's robustness. We find that clustering significantly increases the vulnerability of the system, which is represented by the increased value of the percolation threshold pcp_c in interdependent networks.Comment: 6 pages, 6 figure

    Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China

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    <p/> <p>Background</p> <p>Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas.</p> <p>Methods</p> <p>The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence.</p> <p>Results</p> <p>The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(<it>OR </it>= 1.6, 95%<it>CI </it>(1.042, 2.463), <it>P </it>< 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(<it>P </it>< 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (T<sub>mean</sub>), the average temperature of last two months(T<sub>mean01</sub>) and the average rainfall of current month (R<sub>mean</sub>) and the regression equation was Y = -2.085 + 0.839I<sub>1 </sub>+ 0.998T<sub>mean0 </sub>- 0.86T<sub>mean01 </sub>+ 0.16R<sub>mean0</sub>. All the collected mosquitoes were <it>Anopheles sinensis</it>. The vectorial capacity and the basic reproductive rate of <it>An. sinensis </it>in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively.</p> <p>Conclusion</p> <p>The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of <it>An. sinensis </it>leaded to malaria re-emergence in these areas.</p

    Optimizing Logical Execution Time Model for Both Determinism and Low Latency

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    The Logical Execution Time (LET) programming model has recently received considerable attention, particularly because of its timing and dataflow determinism. In LET, task computation appears always to take the same amount of time (called the task's LET interval), and the task reads (resp. writes) at the beginning (resp. end) of the interval. Compared to other communication mechanisms, such as implicit communication and Dynamic Buffer Protocol (DBP), LET performs worse on many metrics, such as end-to-end latency (including reaction time and data age) and time disparity jitter. Compared with the default LET setting, the flexible LET (fLET) model shrinks the LET interval while still guaranteeing schedulability by introducing the virtual offset to defer the read operation and using the virtual deadline to move up the write operation. Therefore, fLET has the potential to significantly improve the end-to-end timing performance while keeping the benefits of deterministic behavior on timing and dataflow. To fully realize the potential of fLET, we consider the problem of optimizing the assignments of its virtual offsets and deadlines. We propose new abstractions to describe the task communication pattern and new optimization algorithms to explore the solution space efficiently. The algorithms leverage the linearizability of communication patterns and utilize symbolic operations to achieve efficient optimization while providing a theoretical guarantee. The framework supports optimizing multiple performance metrics and guarantees bounded suboptimality when optimizing end-to-end latency. Experimental results show that our optimization algorithms improve upon the default LET and its existing extensions and significantly outperform implicit communication and DBP in terms of various metrics, such as end-to-end latency, time disparity, and its jitter
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