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In this paper, we employ the recent on-line boosting framework to fuse heterogeneous features for object detection and tracking in a video surveillance application. Detection and tracking are treated as a classification problem by an ensemble of weak classifiers built on heterogeneous feature types and updated on-line. We extend the on-line boosting framework by proposing an algorithm that builds...
Image fusion is the procedure of combining useful features from multiple sensor image inputs to a single composite image. In this work, the authors revise the previously proposed image fusion framework, based on self-trained independent component analysis (ICA) bases. In the original framework, equal importance was given to all input images in the reconstruction of the ldquofusedrdquo imagepsilas...
We address here the problem of supervised classification using belief functions. In particular, we study the combination of non-independent sources of information. In a companion paper, we showed that the cautious rule of combination may be best suited than the widely used Dempsterpsilas Rule to combine classifiers in the case of real data. Then, we considered combination rules intermediate between...
The problem of decision fusion in wireless sensor networks for distributed detection applications has mainly been considered in scenarios where sensor observations are conditionally independent and both local sensor statistics as well as wireless channel conditions are available for fusion rule design. In this paper, kernel-based learning algorithms for the design of decision fusion rules are presented...
In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel...
Change detection is an important task for remote monitoring, fault diagnostics and system prognostics. When a fault occurs, it will often times cause changes in measurable quantities of the system. Early detection of changes in system measurements that indicate abnormal conditions helps the diagnostics of the fault so that appropriate maintenance action can be taken before the fault progresses, causing...
Ensemble classifiers are known to generally perform better than each individual classifier of which they consist. One approach to classifier fusion is to apply Shaferpsilas theory of evidence. While most approaches have adopted Dempsterpsilas rule of combination, a multitude of combination rules have been proposed. A number of combination rules as well as two voting rules are compared when used in...
In this paper, a fuzzy pattern classification tuning approach is proposed, which is based on fusion concept. In this method, tuning parameters are learned in a training procedure, enabling system to be capable of managing individual classification task. Fuzzy c-means, as a specific instance of Tuning Reference, is employed as a tool to offer membership function which is used for making decisions and...
Wireless sensor networks are deployed for the purpose of sensing and monitoring an area of interest. Sensors in the sensor network can suffer from both random and systematic bias problems. Even when the sensors are properly calibrated at the time of their deployment, they develop drift in their readings leading to erroneous inferences being made by the network. The drift in this context is defined...
We report here on our effort to investigate the types of hard/soft information that can be realistically collected in an urban operational environment and to generate a data set that can be used for the development of hard/soft data fusion algorithms. Specifically, we discuss: 1) sources of ldquohard informationldquo (i.e. information from physics-based sources) and ldquosoft informationrdquo (i.e...
Considering latest improvements, there are different applications for data fusion techniques. In food transportation systems, measuring environmental conditions like temperature and humidity is necessary for monitoring and controlling quality of products. Application of data fusion on measured data increases reliability of food transportation system. This paper introduces application of data fusion...
Todaypsilas asymmetric threats put new challenges on military decision making. As new technology develops we have new possibilities to support decision making in such environments. However, it is important that the tools developed take into account userspsila (commanderspsila) decision needs. This paper presents some initial user studies of Swedish commanders testing a prototype application developed...
Sensors working at different times, locations, and scales, and experts with different goals, languages, and situations, may produce apparently inconsistent image labels that are reconciled by their implicit underlying relationships. Even when such relationships are unknown to the user, an ARTMAP information fusion system discovers a hierarchical knowledge structure for a labeled dataset. The present...
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