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 wireless sensor networks, sensor nodes are spread randomly over the coverage area to collect information of interest. Data fusion is used to process these collected information before they are sent to the base station, the observer of the sensor network. We study the security of the data fusion process in this work. In particular, we propose a witness-based solution to assure the validation ...

The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings fr...

ata fusion is a paradigm for integrating data from multiple sources to synthesize new information such that the whole is greater than the sum of its parts. This is a critical task in contemporary and future systems that have distributed networks of lowcost, resource-constrained sensors [1], [2]. Current techniques for data fusion are based on general principles of distributed systems and rely o...

Information from different sensors can be fused in various ways. It is often difficult to choose the most suitable method for solving a fusion problem. In a measurement situation, the measured signal is often corrupted by disturbances (noise, etc.). It is, therefore, meaningless to compare crisp values without the corresponding uncertainty intervals. This paper describes a toolbox including nin...

Due to the falling price and availability of sensors, information capture and processing at a realtime or soft realtime rate is emerging as a dominating application space. This class includes interactive multimedia, robotics, security and surveillance applications and many more. A common denominator of these applications is fusion of data gathered by various sensors and data aggregators. In thi...

Decentralized sensor networks are collections of individual local sensors that observe a common phenomenon, quantize their observations, and send this quantized information to a central processor (fusion center) which then makes a global decision about the phenomenon. Most of the existing literature in this field consider only the data fusion aspect of this problem, i.e., the statistical hypoth...

It is now generally recognized that sensor-fusion is the best approach to the accurate construction of environmentmaps by a sensor-equippedmobile robot. Typically, range data collectedwith a range sensor is combined with the reflectance data obtained from one or more cameras mounted on the robot. In much of the past work on sensor fusion in hierarchical approaches to map construction, the fusio...

Multimedia data fusion in wireless sensor networks has attracted great attention in the literature. However the existing data fusion does not take into account the cooperative redundancy of audio data. In order to improve energy efficiency and extend network lifetime, the paper presents an integrated audio data fusion framework, which combines wavelet transform with seamless audio-editing techn...