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This paper considers the problem of decentralized localization in wireless sensor networks (WSNs). The problem is set by combining both radio-fingerprints and accelerometer information. It is then resolved in a decentralized manner where the surveillance area is divided into several zones equipped with calculators. The proposed algorithm consists of computing first estimates using received signal...
This paper is focused on the decentralized localization problem of mobile sensors in wireless sensor networks. Based on a combined localization technique, it uses accelerometer, gyroscope and fingerprinting information to solve the positioning issue. Using the sensors mobility, the proposed method computes first estimates of sensors positions. It then proceeds to a decentralized localization scheme,...
This paper considers the localization problem of sensors in mobile wireless sensor networks. It proposes a combined localization technique, using both fingerprinting and accelerometer information. The proposed approach consists of two phases. In the first one, a power map is constructed over the surveillance area. In the second phase, nodes are localized and a first position estimate is computed using...
This paper proposes a method for background modeling and foreground detection in video. This method divides the background into two layers, the dynamic layer and the static layer. An energy descriptor is proposed to analysis the motion state in dynamic layer while a grid filter is proposed to reduce the negative impact of sudden illumination change such as light switching off. Experiment results compared...
Human matching between different fields of view is a difficult problem in intelligent video surveillance; whereas fusing multiple features has become a strong tool to solve it. In order to guide the fusion scheme, it is necessary to evaluate the matching performance of these features. In this paper, four typical features are chosen for the evaluation. They are the color histogram, UV chromaticity,...
Human matching is fundamental in human tracking over non-overlapping cameras. Fusing multiple features is an efficient way to increase the ratio of matching. In this paper, we present an algorithm of iterative widening fusion (IWF) to fuse the multiple features, including color histogram, UV chromaticity, major color spectrum histogram and scale-invariant features (SIFT). Also, the Bayesian framework,...
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