Abstract. Detecting, locating, and tracking people in a dynamic environment is important in many applications, ranging from security and environmental surveillance to assistance to people in domestic environments, to the analysis of human activities. To this end, several methods for tracking people have been developed using monocular cameras, stereo sensors, and radio frequency tags. In this paper we describe a real-time People Localization and Tracking (PLT) System, based on a calibrated fixed stereo vision sensor. The system analyzes three interconnected representations of the stereo data (the left intensity image, the disparity image, and the 3-D world locations of measured points) to dynamically update a model of the background; extract foreground objects, such as people and rearranged furniture; track their positions in the world. The system can detect and track people moving in an area approximately 3 x 8 meters in front of the sensor with high reliability and good precision.
In this article we present an integrated system the domestic care of elderly people which is being developed within the RoboCare project. The system is composed of a network of sensors placed in the environment to reconstruct a global situation and a set of robotic and software agents for controlling the environment. Within this framework, the two main components that we describe in this article are: (1) a people and robot localization and tracking system that exploits stereo vision in order to monitor the positions of robots and persons; (2) a supervision framework that is in charge of collecting information about the distributed sensors and monitoring the activities of the assisted person. This article shows how, starting from these two ingredients, we are developing a system prototype for an "intelligent" environment, which acts as a global monitor surveying an assisted elderly person and reacts to the stimuli coming from the environment in order to control its evolution.
Abstract. Detecting, locating, and tracking people in a dynamic environment is important in many applications, ranging from security and environmental surveillance to assistance to people in domestic environments, to the analysis of human activities. To this end, several methods for tracking people have been developed using monocular cameras, stereo sensors, and radio frequency tags. In this paper we describe a real-time People Localization and Tracking (PLT) System, based on a calibrated fixed stereo vision sensor. The system analyzes three interconnected representations of the stereo data (the left intensity image, the disparity image, and the 3-D world locations of measured points) to dynamically update a model of the background; extract foreground objects, such as people and rearranged furniture; track their positions in the world. The system can detect and track people moving in an area approximately 3 x 8 meters in front of the sensor with high reliability and good precision.
Intelligent Transportation Systems (ITS) have evolved as a key research topic in recent years, revolutionizing the overall traffic and travel experience by providing a set of advanced services and applications. These data-driven services contribute to mitigate major problems arising from the ever growing need of transport in our daily lives. Despite the progress, there is still need for an enhanced and distributed solution that can exploit the data from the available systems and provide an appropriate and real-time reaction on transportation systems. Therefore, in this paper, we present a new architecture where the intelligence is distributed and the decisions are decentralized. The proposed architecture is scalable since the incremental addition of new peripheral subsystems is supported by the introduction of gateways which requires no reengineering of the communication infrastructure. The proposed architecture is deployed to tackle the problem of traffic management inefficiency in urban areas, where traffic load is substantially increased, by vehicles moving around unnecessarily, to find a free parking space. This can be significantly reduced through the availability and diffusion of local information regarding vacant parking slots to drivers in a given area. Two types of parking systems, magnetic and vision sensor based, have been introduced, deployed, and tested in different scenarios. The effectiveness of the proposed architecture, together with the proposed algorithms, is assessed in field trials.
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