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Combining the static feature and the dynamic path in consecutive image array of small targets, this paper proposes a detecting method for small targets in sonar image: Improving the selection of (SRG) seeded region growing method, and defining the size of searching sub window, this paper realizes the selection of suspected targets in single image that have certain SRR (signal-to-reverberation ratio),...
In Mean Shift algorithm, the features of the tracked target and the image matching similarity criterion have great influence on the result of tracking. a new algorithm of target tracking is proposed. the algorithm combine local binary pattern and color information to form a new feature CL, which tracks target by using a method of centroid iteration based on maximum posterior probability. Thanks to...
In mobile sensing for target localization and tracking, the geometric relationship between sensor nodes and a target may affect the positioning accuracy, of which the effect may be indicated by geometric dilution of precision (GDOP). In the paper, a target localization scheme based on GDOP for time-difference of arrival mobile sensing systems is presented. To attain the best sensor formation for maintaining...
This paper presents tracking algorithms of a mobile robot that tracks a human in front. The mobile robot, which is a differential-driven wheel type, is equipped with a laser range finder to perform human tracking in front. Initially, we recommend the torso part for the robust tracking of the human body in outdoor environment by a laser range finder. To track a human in front, we define a virtual target...
The extended Kalman filter (EKF) is an important tool in wireless sensor networks for localization and tracking of a dynamic target. The performance of the EKF is heavily dependent on the mathematical model used for target dynamics. Significant research has been done for finding an optimum state estimation model for target motion. In this paper we propose a new mobility model for target movement simulations...
In this contribution we present a method for handling merged detections in video-based Multi-Target-Tracking applications. Merged detections occur when two or more objects evoke one joint detection, i.e. when measurements stemming from multiple objects cannot be resolved by the sensor. In video-based applications this is the case when the segmentation fails to separate blobs belonging to different...
This paper presents a novel single target particle filter with spawn model and particle labeling approach, abbreviated SL-PF. The purpose of this filter is to detect instantaneously occurring target maneuvers, e.g. course changes of maritime targets, and to provide accurate tracking performance before and after the maneuvers. The key idea is to borrow the spawn model from the probability hypothesis...
It is important to stably extract horizon lines for sea-based infrared search and track. Most of the existing solutions for the problems only use single image to detect horizon line. Although this results in good accuracy for some images, it often fails to detect horizons in foggy, occluded environments. In this paper, we propose a novel horizon detection and tracking method that is robust to sensor...
In this paper, we consider the challenging problem of tracking a maneuvering target with abrupt accelerations and introduce a new model based on GARCH process. We formulate the acceleration of dynamic model by stochastic differential equation (SDE) with adaptive coefficients and stochastic volatility. Our adaptive state space approach provides a novel dynamic model that naturally facilitates the physical...
This paper presents a new object recognition strategy for target tracking using extended set-membership filter (ESMF). Before the target recognition algorithms are applied on the sensory information, ESMF is employed to determine the demarcation of a guaranteed searching area in which the true position of the target can be certainly found. Then the target recognition algorithms will work in a smaller...
In this paper, performance of Gauss-Hermite filter (GHF) in bearing only tracking problem has been compared with that of extended Kalman filter (EKF) and unscented Kalman filter (UKF) in terms of estimation accuracy, probability of track-loss and computational efficiency. The performance improvement of the GHF with increase in quadrature points and enhanced robustness compared to EKF and UKF with...
This paper presents an intelligent tracking method for nonlinear maneuvering target by compartmentalizing external noises of 3D maneuvering target. Proposed method makes the filter recognize the maneuvering target as linear one by separating acceleration properly from the overhaul noises. For achieving that, we use the particle swam optimization-fuzzy c-means (PSO-FCM) clustering as the criteria of...
Recently sparse representation has been applied to visual tracker by modeling the target appearance using a sparse approximation over a template set, which leads to the so-called L1 trackers as it needs to solve an ℓ1 norm related minimization problem for many times. While these L1 trackers showed impressive tracking accuracies, they are very computationally demanding and the speed bottleneck is the...
We have investigated the utility of field-of-view adaptation for multimodal sensing in cluttered multi-target environments. Measurement data from multiple integrated sensors are collected at a fusion center, which employs a soft association procedure to integrate them into the estimation procedure. A variance penalty model for the limited fields-of-view property is incorporated into the state estimation...
This paper investigates bias compensation for improving the performance of target tracking using range or range difference measurements. We obtain the Maximum Likelihood estimate of the target position at the current instant and pass it to the Kalman filter as observation to obtain the target track. The nonlinear relationship between the target position and measurements creates bias that can degrade...
Efficient detection and tracking of moving target hidden by walls is of interest for rescue, surveillance and security operations. However, in the process of real-time tracking, there are usually some wrong target locations — noise points in the tracking trajectory. This paper gives a short overview of the complete tracking process with all required phases of radar signal processing. Then the paper...
This paper proposes a class of joint subspace and sparse filtering algorithms with an example application in tracking moving targets in highly reverberant environment. Motivated by recent work in low-rank and sparse matrix decomposition, we have developed filtering algorithms that alternate between tracking the low-rank subspace and estimating the instantaneously sparse components, both of which are...
Locally Orderless Tracking (LOT) is a visual tracking algorithm that automatically estimates the amount of local (dis)order in the object. This lets the tracker specialize in both rigid and deformable objects on-line and with no prior assumptions. We provide a probabilistic model of the object variations over time. The model is implemented using the Earth Mover's Distance (EMD) with two parameters...
This paper presents a method for target detection and tracking of IR images in the application of avian surveillance. As there are many reports of avian mortality due to collision with turbine blades, the detection and tracking of birds at turbine sites is an important issue. In this work, three different background subtraction techniques are first applied to detect moving objects. Otsu thresholding...
In the target tracking and its engineering applications, recursive state estimation of the target is of fundamental importance. This paper presents a recursive performance bound for dynamic estimation and filtering problem, in the framework of the finite set statistics, for the first time. This performance limit is derived based on the meaningful distance error between two random sets, the target...
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