In this paper, we present a multi-modal fusion scheme for tracking and behavior analysis in Smart Home environments. This is applied to tracking multiple people and detecting their behavior. To this end, information from multiple heterogeneous sensors (visual color sensor, thermal sensor, infrared sensor and photonic mixer devices) is combined in a common 3D voxel occupancy grid. Graph cuts are...

In this paper we argue why robust positioning in transportation applications is best achieved by multi-sensor fusion. Furthermore, we suggest that sensor fusion processing be performed in a probabilistic fashion and that in the majority of relevant practical applications one should draw on utility theory in order to make decisions that will be of the highest expected benefit given the current c...

This paper presents a Swarm Intelligence based approach for sensor management of a multi sensor networks. Alternate sensor configurations and fusion strategies are evaluated by swarm agents, and an optimum configuration and fusion strategy evolves. An evolutionary algorithm, particle swarm optimization, is modified to optimize two objectives: accuracy and time. The output of the algorithm is th...

In this paper, a multi-sensor information fusion steady-state Kalman estimator for discrete time stochastic linear systems with system errors and sensor errors is presented. Gevers-Wouters(G-W) algorithm is used in this paper. Steady-state Kalman estimator is presented in this paper avoids the complex Diophantine equation, and it is based on the ARMA model to compute the steady-state Kalman est...

Multi-sensor data fusion plays an essential role in most robotic applications. Appropriate registration of information from different sensors is a fundamental requirement in multi-sensor data fusion. Registration requires significant effort particularly when sensor signals do not have direct geometric interpretations, observer dynamics are unknown and occlusions are present. In this paper, we p...

Sensors, which monitor the surrounding environment in order to enhance our decisions, play a major role in our lives and contribute to our actions. A single sensor, however, is not capable of providing enough information; therefore, multiple sensors have to be integrated in a way to perform the additional task of interpretation, which may be more helpful and informative than what can be observe...

In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multisensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enabl...

It is a interesting topic of tracking a 3D object and estimating its 3-D motion in a multi-sensor observation environment. The motion with constant translation velocity and constant rotation rate is assumed and tracked by two separate cameras. Hence the problem considered here also involves a track-to-track fusion system in which twosensors are tracking the same target. Due to the nonlinear nat...

this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The propo...