Towards human-like and transhuman perception in AI 2.0: a review <s> A typical application paradigm: urban intelligent surveillance system <s> For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed into various forms for different stakeholders. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven intelligent transportation system (D2ITS) : a system that is vision, multisource, and learning algorithm driven to optimize its performance. Furthermore, D2ITS is trending to become a privacy-aware people-centric more intelligent system. In this paper, we provide a survey on the development of D2ITS, discussing the functionality of its key components and some deployment issues associated with D2ITS Future research directions for the development of D2ITS is also presented. <s> BIB001 </s> Towards human-like and transhuman perception in AI 2.0: a review <s> A typical application paradigm: urban intelligent surveillance system <s> Home security has been a concern of worldwide. The need of security systems is considered as one of the important aspects of our modern life, people are using such systems to be aware about anything could be happen in their places like their houses when they are away, these system also let them feel more secure and that is what the people really need. As the technology is emerging, abundant home based security systems have been developed and implemented to keep their welfare safe. Video surveillance is an important area of computer vision research, its applications including both outdoor and indoor automated surveillance systems Home security system is an essential mean of protecting our home from illegal invasion. A conventional home security system consists of a Closed Circuit Television, CCTV and burglar alarm which can be replaced by computer based systems with the capability of smarter detection and alert system. In the context of smart home environments, the In-House Video Surveillance systems have as main goal to control the safety and the security of materials and of people living in a domestic environment. This paper provides an overview of various methods and techniques that address the problems of representation, recognition and learning of events, actions and activities of inhabitants from a demotic environment. <s> BIB002 </s> Towards human-like and transhuman perception in AI 2.0: a review <s> A typical application paradigm: urban intelligent surveillance system <s> Automated scene analysis has been a topic of great interest in computer vision and cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded scene analysis has attracted much attention. However, the visual occlusions and ambiguities in crowded scenes, as well as the complex behaviors and scene semantics, make the analysis a challenging task. In the past few years, an increasing number of works on the crowded scene analysis have been reported, which covered different aspects including crowd motion pattern learning, crowd behavior and activity analyses, and anomaly detection in crowds. This paper surveys the state-of-the-art techniques on this topic. We first provide the background knowledge and the available features related to crowded scenes. Then, existing models, popular algorithms, evaluation protocols, and system performance are provided corresponding to different aspects of the crowded scene analysis. We also outline the available datasets for performance evaluation. Finally, some research problems and promising future directions are presented with discussions. <s> BIB003
Public security is a growing problem for cities worldwide. A smart city should first be a safe city. To this end, urban surveillance is becoming increasingly important in a modernized safe city. With the fast development and deployment of all kinds of digitalized devices in every aspect of people's daily life, intelligent surveillance systems and the Internet of Things are drawing extensive attention from both research and industrial communities. Governments from the US, Canada, the EU, Japan, and China have all launched a series of related projects to improve the social and public security. By 2014, there were more than 300 cities around the world that aimed to build an intelligent city  . Global transnational corporations like IBM, Cisco, Siemens, Huawei, and Hikvision have invested enormously in the study and development of related solutions and products for intelligent surveillance systems. From a technological perspective, an urban surveillance system usually involves a set of independent or weakly related sub-systems such as traffic monitoring systems BIB001 , crowd analysis systems BIB003 , criminal tracking systems  , and property protection systems BIB002 . These sub-systems focus mainly on multi-source heterogeneous information processing, e.g., exploiting potential information behind surveillance video data to organize it into a structured video surveillance repository. However, they always encounter different sorts of bottlenecks in handling the scenarios of spatio-temporal large-span sensing, multi-layer multi-view analysis, and multi-source heterogeneous information fusion from a panoramic view. Therefore, there is an urgent need to promote an accelerated development of urban surveillance systems in order to reach a new fully intelligent surveillance sensing and reasoning engine.