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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...
In this paper, a precise description of the threat evaluation process is presented. This is followed by a review describing which parameters that have been suggested for threat evaluation in an air surveillance context throughout the literature, together with an overview of different algorithms for threat evaluation. Grounded in the findings from the literature review, a threat evaluation system have...
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...
Many acoustic factors can contribute to the classification accuracy of ground vehicles. Classification based on Acoustic information fusion for ground vehicle classification a single feature set may lose some useful information. To obtain more complete knowledge regarding vehiclespsila acoustic characteristics, we propose a fusion approach to combine two sets of features, in which various aspects...
This paper considers the problem of the classification of objects observed by vehicle embedded sensors. We propose a general architecture and an algorithm to perform multisensor fusion for the classification purpose. The proposed solution has to be robust and flexible. The robustness is essential because this system is for safety applications. The flexibility is ensured by a modular architecture alongside...
In this paper, we present various approaches for combining classifiers to improve classification of textured images, which are not generally used in this application framework. This is what we call post-classification step of textured images. Three approaches to combine classifiers are presented: the majority voting approach, belief approach, and classification-based approach. Belief, majority voting...
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...
We give a range of techniques to effectively apply on-line learning algorithms, such as Perceptron and Winnow, to both on-line and batch fusion problems. Our first technique is a new way to combine the predictions of multiple hypotheses. These hypotheses are selected from the many hypotheses that are generated in the course of on-line learning. Our second technique is to save old instances and use...
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...
Detecting unknown worms is a challenging task. We propose an innovative technique for detecting the presence of an unknown worm based on the computer measurements extracted from the operating system. We designed an experiment to test the new technique employing several computer configurations and background applications activity. During the experiments 323 computer features were monitored. Four feature...
Ground targets are constrained on the Earth with their velocity vector direction aligned mostly along the body longitudinal axis. The pose angle therefore carries kinematic information useful for tracking maneuvering targets. For target identification (ID), range profiles obtained by a high range resolution (HRR) radar are compared with reference templates in pose angle per target class, thus producing...
Shape-based image retrieval has demonstrated encouraging results in retrieving images based on their content. A large body of research in this area has focused on finding effective shape descriptors to search for query images. Nevertheless, the boundless image content variation makes it impossible for a particular choice of descriptor and an algorithm to be effective for all types of images. It is...
This document describes what particular pieces of information about source should be taken into account to get a reasonable assessment of an attribute information retrieved based on the sensor data or human originated information. It has been proven that actual sensor weights and hypotheses masses do not change randomly, but they vary in time according to tracked target motion, however not directly...
Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call the security personnel in case of anomalies. We are describing the concept and the realization of an indoor security assistance system for real-time decision support. Data for the classification of persons are provided by chemical sensors detecting hazardous materials...
Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call security personnel in case of anomalous events in the surveillance area. We are describing the concept and the realization of an indoor security assistance system for real-time decision support. The system consists of a computer vision module and a person classification...
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