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Haptic guidance has previously been employed to improve human performance in control tasks. This paper presents an experiment to evaluate whether haptic feedback can be used to help humans learn a compensatory tracking task. In the experiment, participants were divided into two groups: the haptic group and the no-aid group. The haptic group performed a first training phase with haptic feedback and...
This paper extends the smoothing algorithm based on integrated probabilistic data association to track multiple maneuvering targets by applying smoothing to joint integrated probabilistic data association (JIPDA). The proposed algorithm utilizes smoothing data association to obtain smoothing prediction which is needed to calculate the smoothing data association probabilities, the smoothing target...
The article focuses on the research of multiple object tracking of the pedestrian in surveillance video sequence. We apply the tracking-by-detection algorithm framework to tracking, and the algorithm kernel is formulating multiple object tracking as an energy minimization problem. The main research emphasis is the construction of energy function which is expected to represent the real-world scenes...
The analytic video is a very challenging area of research in computer vision. Ensure a high level of security in a public space monitored by a surveillance camera is a difficult task in recent years. Understanding people behaviors in real time allows the surveillance systems to analyze unusual events through the video frames. In this paper, we propose a new approach for detecting suspicious behavior...
Random finite set (RFS) based approaches in multi-target filtering are well-established to estimate the states and its number. However, RFS-based approaches have not given the labels of the states over the time which help to produce the trajectories of targets in multi-target tracking. This paper discusses the limitation of the label RFS (LRFS) approach introduced in [1] where an LRFS is an RFS whose...
In this paper we introduce a new method of deciding, if a trajectory is following a pre-defined path. This is achieved by representing hypotheses as trajectories themselves using Accumulated State Densities. Live tracking data is incorporated into the trajectories via out of sequence processing. Through this, we gain two representations of the sensor data, each conditioned on a hypotheses. By using...
In this paper, a single object tracking method based on fusion of detection information collected from a distributed heterogeneous sensor network is proposed. The considered sensor network is composed of one active type source and multiple receivers. It is assumed that the heterogeneous network is capable of acquiring both passive and active information simultaneously. By means of fusion of the acquired...
In this paper we propose an algorithm for multiple object tracking, a heavily researched but still challenging problem of computer vision. We follow the tracking by detection paradigm in an online fashion and formulate tracking as a typical assignment problem between detections and existing tracks that is solved by a modification of the Hungarian algorithm. Contrary to other methods that use a multitude...
Multistatic radar system has a great potential for human detection and tracking for its fine localization precision, wide coverage and good observability. Traditional human detection and tracking are performed on the one dimensional (1-D) range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets and obtain the measurements for target tracking. It can...
We formulate multiple object tracking (MOT) as a Generalized Maximum Multi Clique problem (GMMCP) without any simplified version in problem formulation or optimization, which makes full use of image evidence. Afterwards, we solve the GMMCP through Mixed Binary-Integer Program (MBIP) and obtain the final motion trajectories of the multiple objects. In order to improve the algorithm's performance, we...
Visual Multiple Object Tracking (VMOT) is an important computer vision task which has gained increasing attention due to its academic and commercial potential. There are many different approaches have been proposed to solve the problem. Compared with single object tracking which focuses on appearance model, motion model and other factors, multiple object tracking shares these common challenges, and...
In order to address the problem of detecting and tracking very low observable (VLO) targets in heavy clutter, a fast ergodic Hough transform (FEHT) algorithm is proposed. The contributions consist of three aspects. First, the FEHT does not invoke a random combination but rather an ergodic combination of all possible measurement pairs to generate the line parameters, which avoids the failure detection...
This paper addresses the dim target tracking problem with respect to the multi-frame detection (MFD). Generally, the MFD strategy implicitly merges the tracking stage into its framework, by which the estimated target trajectory can be simultaneously returned when a target is declared. However, due to the batch processing manner of MFD, such products, essentially, are short state sequences in time...
The problem of target detection via dynamic programming based track before detect (DP-TBD) is considered in this paper. DP-TBD is a batch processing method that jointly processes the multiple consecutive frames of measurements in the processing window (PW). Due to this, when target-originated measurements becomes available after the PW beginning, DP-TBD has a detection latency problem, since the merit...
In air traffic control (ATC), aerial vehicles normally travel within scheduled route channels with certain probabilities. Exploitation of the probability-constrained route information intuitively will lead to enhancement of tracking accuracy and tracking continuity. This paper presents an ATC tracking approach by incorporating such information to improve the estimation performance accordingly. First,...
A new end-point-constrained spherical extended Kalman filter is presented for tracking near-radially inbound maneuvering targets. The performance of this new filter is compared to that of both Cartesian and spherical extended Kalman filters for a target that undergoes a set of 15 g maneuvers in all dimensions. Subsonic and supersonic maneuvering targets are considered with a low update period rotating...
In this paper we propose a novel solution to the labeled multi-target tracking problem. The method presented is specially effective in scenarios where the targets have once moved in close proximity. When this is the case, disregarding the labeling uncertainty present in a solution (after the targets split) may lead to a wrong decision by the end user. We take a closer look at the main cause of the...
We consider a target tracking problem where, in addition to the usual sensor measurements, accurate observations with uncertain timestamps are available. Such observations could, e.g., come from traces left by a target or from witnesses of an event, and have the potential in some scenarios to improve the accuracy of an estimate significantly. The Bayesian solution to the smoothing problem for one...
The precession feature of space target provides an effective approach for target recognition. However, with the requirements that target detection and tracking to be completed successfully before the processing of precession features extraction can be implemented, the existing methods demand radar resources allocation for target detection, tracking and feature extraction, respectively, thus reducing...
There is great potential for the application of Microaerial vehicles (MAVs) in the field of civil and military. Robust trajectory tracking control ability is fundamental for flying tasks. However, MAV is an under-actuated, nonlinear and strong coupling system and it usually endures frequent disturbances while flying. These factors make precise trajectory tracking control of MAV very difficult. The...
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