A frequent trajectory patterns mining algorithm is proposed to learn the object activities and classify the trajectories in intelligent visual surveillance system.The distribution patterns of the trajectories were gen...A frequent trajectory patterns mining algorithm is proposed to learn the object activities and classify the trajectories in intelligent visual surveillance system.The distribution patterns of the trajectories were generated by an Apriori based frequent patterns mining algorithm and the trajectories were classified by the frequent trajectory patterns generated.In addition,a fuzzy c-means(FCM)based learning algorithm and a mean shift based clustering procedure were used to construct the representation of trajectories.The algorithm can be further used to describe activities and identify anomalies.The experiments on two real scenes show that the algorithm is effective.展开更多
This paper deeply studies the intelligent Home embedded system based on B/S architecture. Firstly, analysis requirement of Home function based on the existing software development mode, and proposed a system framework...This paper deeply studies the intelligent Home embedded system based on B/S architecture. Firstly, analysis requirement of Home function based on the existing software development mode, and proposed a system framework of intelligent Home system, and designed the communication scheme of the whole Home system, also gives the system each function module realization. This paper achieve two basic service system based on Intelligent Home through a series of analysis and design： outdoor remote intelligent Home monitoring service and the indoor intelligent management service.展开更多
This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmati...This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmatic actions cannot deal with the unpredictable nature of many risk dynamics, an attempt to improve the current approach for safety management in the construction industry will be presented in this paper. To this aim, the features offered by Bayesian networks have been exploited. The present research has led to the definition of a probabilistic model using elicitation techniques from subjective knowledge. This model, which might be meant as a reliable knowledge map about accident dynamics, showed that a relevant part of occurrences fall in the ＂hardly predictable hazards＂ category, which cannot be warded off by programmatic safety measures. Hence, more effort turned out to be needed in order to manage those hardly predictable hazardous scenarios. Consequently, further developments of this research project will focus on a real time monitoring system for the identification of unpredictable hazardous events in construction.展开更多
基金National High-Tech Research and Development Plan of China(No.2003AA1Z2130)Science and Technology Project of Zhejiang Province of China(No.2005C1100102)
文摘A frequent trajectory patterns mining algorithm is proposed to learn the object activities and classify the trajectories in intelligent visual surveillance system.The distribution patterns of the trajectories were generated by an Apriori based frequent patterns mining algorithm and the trajectories were classified by the frequent trajectory patterns generated.In addition,a fuzzy c-means(FCM)based learning algorithm and a mean shift based clustering procedure were used to construct the representation of trajectories.The algorithm can be further used to describe activities and identify anomalies.The experiments on two real scenes show that the algorithm is effective.
文摘This paper deeply studies the intelligent Home embedded system based on B/S architecture. Firstly, analysis requirement of Home function based on the existing software development mode, and proposed a system framework of intelligent Home system, and designed the communication scheme of the whole Home system, also gives the system each function module realization. This paper achieve two basic service system based on Intelligent Home through a series of analysis and design： outdoor remote intelligent Home monitoring service and the indoor intelligent management service.
文摘This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmatic actions cannot deal with the unpredictable nature of many risk dynamics, an attempt to improve the current approach for safety management in the construction industry will be presented in this paper. To this aim, the features offered by Bayesian networks have been exploited. The present research has led to the definition of a probabilistic model using elicitation techniques from subjective knowledge. This model, which might be meant as a reliable knowledge map about accident dynamics, showed that a relevant part of occurrences fall in the ＂hardly predictable hazards＂ category, which cannot be warded off by programmatic safety measures. Hence, more effort turned out to be needed in order to manage those hardly predictable hazardous scenarios. Consequently, further developments of this research project will focus on a real time monitoring system for the identification of unpredictable hazardous events in construction.
