Due to the increasing demand for developing a secure and smart living environment, the intelligent video surveillance technology has attracted considerable attention. Building an automatic, reliable, secure, and intel...Due to the increasing demand for developing a secure and smart living environment, the intelligent video surveillance technology has attracted considerable attention. Building an automatic, reliable, secure, and intelligent video surveillance system has spawned large research projects and triggered many popular research topics in several international conferences and workshops recently. This special issue of Journal of ElecWonic Science and Technology （JEST） aims to present recent advances in video surveillance systems which address the observation of people in an environment, leading to a real-time description of their actions and interactions.展开更多
This study focuses on the multiphase flow properties of crowd motions.Stability is a crucial forewarning factor for the crowd.To evaluate the behaviors of newly arriving pedestrians and the stability of a crowd,a nove...This study focuses on the multiphase flow properties of crowd motions.Stability is a crucial forewarning factor for the crowd.To evaluate the behaviors of newly arriving pedestrians and the stability of a crowd,a novel motion structure analysis model is established based on purposiveness,and is used to describe the continuity of pedestrians’pursuing their own goals.We represent the crowd with self-driven particles using a destination-driven analysis method.These self-driven particles are trackable feature points detected from human bodies.Then we use trajectories to calculate these self-driven particles’purposiveness and select trajectories with high purposiveness to estimate the common destinations and the inherent structure of the crowd.Finally,we use these common destinations and the crowd structure to evaluate the behavior of newly arriving pedestrians and crowd stability.Our studies show that the purposiveness parameter is a suitable descriptor for middle-density human crowds,and that the proposed destination-driven analysis method is capable of representing complex crowd motion behaviors.Experiments using synthetic and real data and videos of both human and animal crowds have been conducted to validate the proposed method.展开更多
文摘Due to the increasing demand for developing a secure and smart living environment, the intelligent video surveillance technology has attracted considerable attention. Building an automatic, reliable, secure, and intelligent video surveillance system has spawned large research projects and triggered many popular research topics in several international conferences and workshops recently. This special issue of Journal of ElecWonic Science and Technology （JEST） aims to present recent advances in video surveillance systems which address the observation of people in an environment, leading to a real-time description of their actions and interactions.
基金Project supported by the Shenzhen Science and Technology Innovation Council(No.JCYJ20170410171923840)the National Key R&D Program of China(Nos.2019YFB1310403 and 2019YFB1310402)+2 种基金the National Natural Science Foundation of China(Nos.U1613226 and U1813216)the Chinese University of Hong Kong,Shenzhen(No.PF.01.000143)Shenzhen Institute of Artificial Intelligence and Robotics for Society。
文摘This study focuses on the multiphase flow properties of crowd motions.Stability is a crucial forewarning factor for the crowd.To evaluate the behaviors of newly arriving pedestrians and the stability of a crowd,a novel motion structure analysis model is established based on purposiveness,and is used to describe the continuity of pedestrians’pursuing their own goals.We represent the crowd with self-driven particles using a destination-driven analysis method.These self-driven particles are trackable feature points detected from human bodies.Then we use trajectories to calculate these self-driven particles’purposiveness and select trajectories with high purposiveness to estimate the common destinations and the inherent structure of the crowd.Finally,we use these common destinations and the crowd structure to evaluate the behavior of newly arriving pedestrians and crowd stability.Our studies show that the purposiveness parameter is a suitable descriptor for middle-density human crowds,and that the proposed destination-driven analysis method is capable of representing complex crowd motion behaviors.Experiments using synthetic and real data and videos of both human and animal crowds have been conducted to validate the proposed method.
