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Video surveillance has been used extensively in our daily life today, for example, traffic safety, trajectory analysis, event monitoring, and crowd behavior identification. However, sometimes in many real-world video sequences dealing with complex scenario and environmental noise is still a challenging task. One solution is to consider information of scenario during tracking. In this paper, we propose...
We propose a new method to estimate the 6-dof trajectory of a flying object such as a quadrotor UAV within a 3D airspace monitored using multiple fixed ground cameras. It is based on a new structure from motion formulation for the 3D reconstruction of a single moving point with known motion dynamics. Our main contribution is a new bundle adjustment procedure, which in addition to optimizing the camera...
Tracking multiple persons in a monocular video of a crowded scene is a challenging task. Humans can master it even if they loose track of a person locally by re-identifying the same person based on their appearance. Care must be taken across long distances, as similar-looking persons need not be identical. In this work, we propose a novel graph-based formulation that links and clusters person hypotheses...
The optimal combination strategy for two swim-out acoustic decoys to countermeasure acoustic homing torpedo is studied. The kinetics models of torpedo, submarine and decoys are established, followed with homing algorithm and re-search strategy of torpedo. Based on the assessment criterion of decoys playing against acoustic torpedoes, the genetic algorithm is applied to obtain the optimal countermeasure...
In order to solve the problem of high computational complexity in the target tracking, this paper combines mean shift with the particle filter algorithm. The detailed process of establishing the target model is proposed. According to the results, the approach can constantly detect the exact position of target. Experimental results show that the proposed method has better performance compared with...
Accurately and reliably tracking the 3D position and orientation of individuals in large flying swarms is valuable not only for scientific researches but also practical applications. However, large quantity, frequent occlusions, similar appearance, tiny body size and abrupt motion make it remain an open problem. The 3D flying swarm tracking method proposed in this paper tracks both position and orientation...
Tracking-by-detection has become a popular tracking paradigm in recent years. Due to the fact that detections within this framework are regarded as points in the tracking process, it brings data association ambiguities, especially in crowded scenarios. To cope with this issue, we extended the multiple hypothesis tracking approach by incorporating a novel enhancing detection model that included detection-scene...
A problem of state estimation with destination constraint is considered in this paper. An anti-radiation missile (ARM) often moves towards the target along a trajectory which is almost linear in the X-Y plane. The linear constraint for trajectory and target position are known as priori and can be used to enhance the performance of a tracking filter. In this paper, a destination constrained Kalman...
Conventional point object model based automotive radar tracking system assumes at most one detection received from the target object at a time. However, in real applications for an extended object, such as a passenger car, located within a close range to a high-resolution radar or LIDAR, the system usually receives multiple reflections from different parts of the object. This can introduce large bias...
In this paper, we investigate cooperative passive sensor trajectory planning for tracking a target where the tracking error is sensor trajectory dependent. We consider the problem under a scenario of tracking a moving target using two unmanned bearings-only sensors. The basic idea is to maximise the target information acquired from the processing measurements of the two sensors by cooperatively scheduling...
Under the common state space model for tracking a maneuvering target, the tracker needs to adapt its state transition model timely to match the target maneuver, which is usually carried out by finding the best one from a bank of candidate Markov models or employing all of them simultaneously but assigning different probabilities. Both methods suffer from time delay for confirming the target maneuver...
This paper proposes an efficient implementation of the multi-sensor generalized labeled multi-Bernoulli (GLMB) filter. The solution exploits the GLMB joint prediction and update together with a new technique for truncating the GLMB filtering density based on Gibbs sampling. The resulting algorithm has a complexity in the order of the product of the number of measurements from each sensor, and quadratic...
We investigate the problem of determining the trajectory that an observer should follow to be able to accurately track a target in a bearings-only measurements context. We assume that the target's motion is uniform and that the measurements are corrupted by an additive Gaussian white noise. Though, in theory, this process is observable if the observer maneuvers with turns or accelerations, the quality...
In this study, we present a set of new evaluation measures for the track-based multi-camera tracking (T-MCT) task leveraging the clustering measurements. We demonstrate that the proposed evaluation measures provide notable advantages over previous ones. Moreover, a distributed and online T-MCT framework is proposed, where re-identification (Re-id) is embedded in T-MCT, to confirm the validity of the...
In multiple-target tracking problem, data association technique plays an significant role. When targets move closely or crosswise, performances of conventional data association algorithms which use kinematic information only may be degraded. Actually, beside the kinematic information, sensors always can obtain feature information about the target, and incorporating the features into data association...
Data association, which could be categorized into offline approaches and the online counterparts, is a crucial part of a multi-object tracker in the tracking-by-detection framework. On the one hand, classical offline data association methods exploit all the video data and have high computation cost, which makes them unscalable to long-term offline video data. On the other hand, online approaches have...
Evaluating the performance of multi-target tracking with respect to tracks rather than unlabeled estimated points is important and challenging. Existing approaches assume exact knowledge of the ground truth. However, this is far from the reality. This paper proposes a method to deal with the case of unknown ground truth by measuring the difference between mock tracks and the assumed targets in the...
This paper proposes a geometric model based lateral control system for a ground vehicle. Lateral control algorithm takes the advantages of two different path tracking methods at different path geometries. Two of the well-known geometric path tracking methods, namely Pure-Pursuit method and Stanley method, are combined with a simple and easy to implement approach. Pure-Pursuit method is very good at...
Multifunction radars (MFR) have to achieve their capability requirements in an increasingly complex environment, populated with diverse and hostile targets (e.g. low RCS, low speed targets in clutter or high speed, ballistic targets) in saturating scenarios (due to e.g. RF interference or threats). These radar systems are increasingly exploiting active electronically scanned array (AESA) technology...
In this work, we propose a novel implementation of the Probability Density Hypotheses (PHD) filter for tracking an unknown number of extended objects. For this purpose, we first show how a recently developed Kalman filter-based method for elliptic shape tracking can be embedded into the Gaussian Mixture PHD (GM-PHD) filter framework. Second, we propose a track labeling method based on a Minimum-Cost...
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