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Using an imaging system with a wide field of view increases situational awareness (peripheral vision) at the expense of reduced image resolution. Ideally, an imager should provide high-resolution imagery around a specific region (or regions) of interest and a wide field of view. This paper proposes a particular approach to address these competing requirements: an image where a narrow field of view...
Advantages in the application of intelligent approaches, such as the conjunction of artificial vision and Unmanned Aerial Vehicles (UAV), have been recently emerging. This paper presents a system capable of detecting ground vehicles through aerial images taken by a UAV in real time. In addition, the system offers the possibility to autonomously guide the UAV to keep track of a vehicle that has been...
This paper presents the experimental application of an autonomous mobile robot for gas leak detection in indoor environments. The application is focused to automatize a human-risky operation in indoor areas. The goal of the autonomous mobile robot is the localization of a toxic gas leak source. So, the mobile robot has to explore the whole area and perform an auto-localization procedure based on a...
We consider a distributed detection system with communication constraints, where several nodes are arranged in an arbitrary tree topology, under the assumption of conditionally independent observations. We propose a cyclic design procedure using the minimum expected error probability as a design criterion while adopting a person-by-person methodology. We design each node jointly together with the...
Automated recognition of individuals can be performed using biometrics without any requirement of explicit knowledge of a PIN or a password. On the one side biometrics has given convenience to citizens as they do not need to memorize a bunch of passwords, but on the other side intra (inter) class variations within (between) biometric features makes biometric authentications untrustworthy. Therefore,...
In this work we dig into the problem of recurring concept drifts, proposing a framework to manage them. Its implementation and evaluation phases have been oriented to solve the spam detection problem, taking into account that it is a real-world situation where concepts (spam patterns) may reappear. The possibility of detecting recurring drifts allows to reuse previously learnt models, enhancing the...
In this work, a general information fusion problem is formulated as an optimisation protocol in the space of probability measures (i.e. the so-called Wasserstein metric space). The highlevel idea is to consider the data fusion result as the probability measure that is closest to a given collection of input measures in the sense that it will minimise the (weighted) Wasserstein distance between itself...
In this paper, the differential privacy problem in parallel distributed detections is studied in the Bayesian formulation. The privacy risk is evaluated by the minimum detection cost for the fusion node to infer the private random phenomenon. Different from the privacy-unconstrained distributed Bayesian detection problem, the optimal operation point of a remote decision maker can be on the boundary...
This paper presents a distributed solution for multi-object tracking and classification. The state of objects is partially observed by a set of sensors organized in a network. The idea is to exchange partial data throughout the network and provide a complete information at each sensor level. The proposed solution involves a finite time average consensus where existing solutions are based on asymptotic...
Autonomous underwater vehicle (AUV) platforms are low-cost devices with respect to conventional detection and tracking systems for the purpose of anti-submarine warfare (ASW). Unfortunately, the increased level of manageability is often paid in terms of capabilities, e.g., limited speed and endurance, inferior sensor payloads, and so on. This work exploits two fundamental concepts aimed at filling...
Image stabilization is relevant for various industrial and medical applications. In particular, we consider the use of image stabilization in robotic beating heart surgery. A robot, which is remotely controlled by the surgeon, can automatically compensate for the motion of the beating heart. To give the surgeon the illusion of operating on a stationary heart, a stabilized image of the beating heart...
Academic communities need a collaborative portal to provide new distance learning opportunities and to improve personal training opportunities. An innovative portal must integrate an adaptive engine to assist learners individually, meeting them at their skill and knowledge levels. More than 300 biomedical students were enrolled to carry out the assessment of the new developed platform, which integrates...
Detecting and tracking people and groups of people is a key skill for intelligent vehicles, interactive systems and robots that are deployed in humans environments. In this paper, we address the problem of detecting groups of people from learned social relations between individuals with the goal to reliably track group formation processes. Opposed to related work, we track and reason about multiple...
This paper presents a novel approach to the fusion of nonlinear motion dynamics for 2D target tracking applications in video analytics by using Fokker-Planck equation (FPE) and the projection filter. The motion dynamics of the target is first conveniently represented using the corresponding FPE for the state posterior. The motion dynamics is then fused into target tracking process to reliably predict...
The scheduling of track dwells to minimize radar energy and time with an agile beam radar is considered. Typically, a radar scheduler picks a waveform pulsewidth to achieve a desired signal-to-noise (SNR) level, and this is called the nominal tracking SNR. In theory, the combination of high quality measurements and good kinematic modeling in the tracker yields longer track revisit periods, thus minimizing...
Improved sensors in the automotive field are leading to multi-object tracking of extended objects becoming more and more important for advanced driver assistance systems and highly automated driving. This paper proposes an approach that combines a PHD filter for extended objects, viz. objects that originate multiple measurements while also estimating the shape of the objects via constructing an object-local...
In this paper, we consider data obeying sequentially two equations corresponding to two different models. The time of model change and the parameters of each model are unknown. We propose a non-recursive estimation of this time and of the parameters. A Cram??r-Rao-type lower bound for this time is proposed. Several applications, including target motion analysis problems, are given.
The performance of the nearest-neighbor (NN) classifier is known to be very sensitive to the distance metric used in classifying a query pattern, especially in scarce-prototype cases. In this paper, a pairwise-weighted (PW) distance metric related to pairs of class labels is proposed. Compared with the existing distance metrics, it provides more flexibility to design the feature weights so that the...
In this work, we present Simul-A2, a simulator based on a multi-agent architecture. Using this simulator, we can make test with Advanced Driver Assistance Systems (ADAS). Simul-A2 has been developed using Webots and libraries that have been developed by ROS Project. In order to introduce more realism, the virtual worlds in the simulator contain several agents that control the vehicles regardless of...
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