The Preventive and Active Safety Applications project (PReVENT), contributes to the safety goals of the European Commission (EC). PReVENT addresses the function fields of Safe Speed and Safe Following, Lateral Support, Intersection Safety and Protection of Vulnerable Road Users and Collision Mitigation in order to cover the field of active safety. The majority of these functions are characteriz...

Abstract In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively reg...

From 30.07.06 to 04.08.06, the Dagstuhl Seminar 06311 Sensor Data and Information Fusion in Computer Vision and Medicine in the International Conference and Research Center (IBFI), Schloss Dagstuhl. Sensor data fusion is of increasing importance for many research elds and applications. Multi-modal imaging is routine in medicine, and in robitics it is common to use multi-sensor data fusion. Duri...

In this paper, ‎the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented‎. ‎A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis‎. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...

The multi-sensor fusion can provide more accurate and reliable information compared to information from each sensor separately taken. Moreover, the data from multiple heterogeneous sensors present in the medical surveillance systems have different degrees of uncertainty. Among multi-sensor data fusion techniques, Bayesian methods and evidence theories such as Dempster-Shafer Theory (DST), are c...

The multi-sensor fusion can provide more accurate and reliable information compared to information from each sensor separately taken. Moreover, the data from multiple heterogeneous sensors present in the medical surveillance systems have different degrees of uncertainty. Among multisensor data fusion techniques, Bayesian methods and evidence theories such as Dempster-Shafer Theory (DST), are co...

by Ryan Connaughton Multi-biometrics, or the fusion of more than one biometric modality, sample, sensor, or algorithm, is quickly gaining popularity as a method of improving biometric system performance and robustness. Despite the recent growth in multi-biometrics research, little investigation has been done to explore the possibility of achieving multi-modal fusion from a single sensor. This a...

Basic probability assignment (BPA) has the key role in multi-sensor data fusion. This paper proposed a way to determine BPA using the various signals acquired from the sensors. It described the analysis of signals detected by the sensors. The determined BPA were used for multi-sensor data fusion to infer and recognize the context targeted by a wireless sensor networks. To determine BPA, the cha...

From the intelligent fault diagnosis system requirements, this article analyzes the relationship between the fault diagnosis and the multi-information fusion basing on the summing up the multi-sensor information fusion technology, and studies the hierarchical structure of multisensor information fusion system and the content of integration, and establishes an intelligent fault diagnosis model w...

This paper describes a distributed agent-based paradigm, for hybrid (soft and hard) computation involved in multisensor information (data) fusion. The computations are interpreted as the outcome arising out of deterministic, nondeterministic or stochastic interaction among the agents, in an environment containing multiple sensors. These interactions are like chemical reactions and the evolution...