Keywords: Wireless sensor networks Doppler effect Kalman filter Track association Multiple targets a b s t r a c t This paper introduces an efficient rule-based algorithm for tracking multiple fast-moving ground vehicles in an acoustic Wireless Sensor Network (WSN). To reduce the level of power consumption, the acoustic sensor nodes in the WSN are assumed to be very simple in nature, having no ...

A critical component of a multi-sensor system is sensor scheduling to optimize system performance under constraints (e.g. power, bandwidth, and computation). In this paper, we apply particle filter sequential Monte Carlo methods to implement multiple sensor scheduling for target tracking. Under the constraint that only one sensor can be used at each time step, we select a sequence of sensor use...

This paper presents Markov chain Monte Carlo data association (MCMCDA) for solving data association problems arising in multiple-target tracking in a cluttered environment. When the number of targets is fixed, the single-scan version of MCMCDA approximates joint probabilistic data association (JPDA). Although the exact computation of association probabilities in JPDA is NP-hard, we prove that t...

In this paper, we present an algorithm for determining a velocity probability distribution prior from low frame rate aerial video of an urban area, and show how this may be used to aid in the multiple target tracking problem, as well as to provide a foundation for the automated classification of urban transportation infrastructure. The algorithm used to develop the prior is based on using a gen...

System provisioning is the problem of determining the number of resources required to accomplish a complicated system level task, e.g. tracking or discriminating between N targets. This is a central problem in multi-target tracking with synthetic aperture radars where the number of targets can easily exceed the available resources. This paper treats the following conservative sensor provisionin...

A new interacting multiple model (IMM) algorithm using intelligent input estimation (IIE) is proposed for maneuvering target tracking. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown target acceleration by a fuzzy system using the relation between the residuals of the maneuvering filter and the non-maneuvering filter. The gene...

Tracking multiple people using cameras is similar to the well-studied problem of tracking multiple radar or sonar echoes. This thesis shows that current camera-based tracking algorithms convert each image in a video sequence to a list of targets through a segmentation step, and pass this target set to a traditional multiple-point-target tracking algorithm. Various tracking vision-based strategi...

Tracking objects under occlusion or non-rigid deformation poses a major problem: appearance variation of target makes existing bounding rectangle based representation vulnerable to background noise imported during adaptive appearance update. We address the object tracking problem by exploring superpixel based visual information around the target. Instead of representing each object with a singl...