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Many applications for mobile robot authentication require to be able to explore a large field of view with high resolution. The proposed vision system is composed of a catadioptric sensor for full range monitoring and a pan tilt zoom (PTZ) camera leading to an innovative sensor, able to detect and track any moving objects at a higher zoom level. In our(More)
Our work and living environments are increasingly populated by devices which integrate computational ability and intelligence. The Nomad Biometric Authentication (NOBA) project focuses on the development and implementation of biometric technologies for strong authentication to enable provision of nomadic computing users with services and document(More)
Bio-inspired and non-conventional vision systems are highly researched topics. Among them, omnidirectional vision systems have demonstrated their ability to significantly improve the geometrical interpretation of scenes. However, few researchers have investigated how to perform object detection with such systems. The existing approaches require a(More)
In this paper, we present a car self-localization approach based on free inputs. We propose to use wheel speeds, which is available on most car through the CAN bus, and community developed road maps. A particle filter framework is used to achieve self-localization on a graph-based representation of a road map. Our results suggests that self-localization and(More)
Visual surveillance of dynamic objects, particularly vehicles on the road, has been, over the past decade, an active research topic in computer vision and intelligent transportation systems communities. In the context of traffic monitoring, important advances have been achieved in environment modeling, vehicle detection, tracking, and behavior analysis.(More)
The IRSEEM research institute of ESIGELEC, France wish to contribute its research findings to this W3C workshop from the ongoing research in field of development of augmented reality with the help of computer vision based methods for merging the virtual world as close and as accurate as possible to the real environment. Abstract The paper presents how can(More)
In this paper, we propose a car positioning approach that does not rely on GPS. We propose to use car wheel speeds and road maps in order to achieve robust positioning of the vehicle. The vehicle positioning is achieved by applying particle filtering on a graph-based representation of a road map. We show that the vehicle positioning is feasible and robust(More)