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Cluster tracking under kinematical constraints using random matrices

Cluster tracking under kinematical constraints using random ...

引用

2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Wolfgang Koch Michael Feldmann Information Processing and Ergonomics FGAN Research Institute of Communication Wachtberg Germany

ISBN: (纸本)9780863419102

Collectively moving object clusters are of particular interest in certain applications and have to be tracked as separate aggregated entities consisting of an unknown number of individuals. tracking of convoys or large vehicles in wide area ground surveillance are practically important examples (GMTI: Ground Moving target Indicator). In standard tracking algorithms, the objects of interest are usually considered as point source objects; i. e. compared to the sensor resolution their spatial extension is neglected. Due to the increasing resolution capabilities of modern sensors, however, different scattering centers of an extended object cam cause distinct detections. In this sense also collectively moving object groups can be considered as extended objects. Due to the resulting data association and resolution conflicts. any attempt of tracking individual objects within the group is no longer reasonable. In this paper ellipsoidal object extensions are modeled by random matrices, which are treated as additional state variables to be estimated. An important aspect is the incorporation of context information into the Bayesian data processing formalism. We here consider kinematical constraints such as road maps and sensor specific characteristics such as Doppler-blindness.

关键词： tracking of extended/group/cluster/convoy targets GMTI Road maps Doppler-blindness Random matrices Road maps EXTENDED OBJECTS State variable Large automobiles tracking Resolving power data association matrices

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Population based particle filtering

Population based particle filtering

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2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Harish Bhaskar Lyudmila Mihaylova Simon Maskell The Institution ofEngineering and Technology Lancaster University Stevenage Hertfordshire UK The Institution ofEngineering and Technology QinetiQ Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

This paper proposes a novel particle filtering strategy by combining population Monte Carlo Markov chain methods with sequential Monte Carlo chain particle which we call evolving population Monte Carlo Markov Cham (EP MCMC) filtering. Iterative convergence on groups of particles (populations) is obtained using a specified kernel moving particles toward more likely regions. The proposed technique introduces variety in the particles both in the sampling procedure and in the resampling step. The proposed EP MCMC filter is compared with the generic particle filter, with a population MCMC by A. Jastra et al (2007) and a sequential Monte Carlo sampler. Its effectiveness is illustrated over an example for object tracking in video sequences and over the bearing only tracking problem.

关键词： tracking Particle filter Population based methods MCMC SMC sampler Particle filters Population tracking Filtration Hypoderma particles sampling of program Video sequences Resampling Markov chain ESSENTIAL POWER European Parliament

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Automatic object detection based on adaptive background subtraction using symmetric alpha stable distribution

Automatic object detection based on adaptive background subt...

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2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Harish Bhaskar Lyudmila Mihaylova Alin Achim The Institution ofEngineering and Technology Lancaster University Stevenage UK The Institution ofEngineering and Technology Bristol University Stevenage UK

ISBN: (纸本)9780863419102

Automatic detection of objects is critical to video tracking systems. One of the simplest techniques for detection is background subtraction (BS). BS refers to the process of segmenting moving regions from image sequences. The BS process involves building a model of the background and extracting regions of the foreground (moving objects). In this paper, we propose an extended cluster BS (CBS) technique based on symmetric alpha stable ( SalphaS ) distributions. The developed method functions at cluster-level as against the traditional pixel-level BS methods. An iterative self-adaptive mechanism is presented that allows automated learning of the distribution of the model parameters. The results for the CBS SalphaS algorithm on real video sequences show improvement compared with a CBS using a Gaussian mixture model.

关键词： Automatic object detection tracking Background subtraction Alpha stable distribution Video sequences Video sequences Object detection Bahamas Subtraction CYCLOHEXYL BENZOTHIAZYL SULPHENAMIDE CBS gene tracking CENTROSYMMETRIC automatic detection

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tracking with inter-visibility variables

Tracking with inter-visibility variables

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2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Paul Horridge Simon Maskell QinetiQ UK QinetiQ

ISBN: (纸本)9780863419102

This paper is concerned with the problem of tracking targets where each sensor in the network's view of the target is prone to obscuration due to other objects in the environment. An off-the-shelf multi-sensor tracker that attempts to localize (i.e. triangulate) targets moving through such a sensor network (for example, a CCTV network) assumes a fixed probability of detection for each sensor. This assumption is not valid when obscuration becomes pronounced and results in a degradation of performance. The tracker typically underestimates the probability of a track being present which causes premature track termination and thereby track fragmentation. One approach to countering this effect is to assume that a map of the environment is available and can be used to determine the probability of detection for any given hypothetical target position and given sensor position. This approach necessitates access to such a map, which may not be readily available. To address this issue, this paper build on the recent development of algorithms for estimating the probability of targets' existence (for track management) to propose a model that considers random variables associated with the time-varying inter-visibility of targets from sensors. We compare this proposed approach, the use of known maps and the use of off-the-shelf multi-sensor tracking algorithms using simulated data. Recommendations include the development of a framework for feedback to and from a perceived map, built up over time. The technical challenges associated with the robust sequential estimation of an unknown and fixed (or slowly varying) map are highlighted.

关键词： tracking Triangulation CCTV Existence Obscuration Inter-visibility CLOSED CIRCUIT TELEVISION OCCULTATIONS tracking triangulation maps targets Sensors Probability Sensor networks degradation of performance Track

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Fussion of novel biometrics for human tracking and identification

Fussion of novel biometrics for human tracking and identific...

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2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Jo Nothard John Hargreaves Michela Goffredo Mark Nixon John Carter Dan Pearce Chris Harvey Cody Technology Park QinetiQ Limited Farnborough Hampshire UK ISIS Electronics and Computer Science University of Southampton UK

QinetiQ and Southampton University are engaged in a programme on fusion of novel biometrics for real-world secure environments. The main objective is to develop a camera system for measuring and fusing two key biometrics: gait and hyperspectral signature; for use outdoors, at a distance and in real world scenarios. It will provide a capability to automatically track and identify key individuals remotely and covertly by 3-D analysis of their gait and their spectral signature. This offers a significant tactical advantage over current biometrics systems which either require a cooperative subject or are unreliable in real world scenarios. The programme to date has concentrated upon the core technologies prior to incorporation into a single biometric system and fusion of the respective characteristics. Achievements so far include verification of techniques for 3D gait reconstruction from a single camera, trials of a 16 band IRIS (image replicating imaging spectrometer) camera sub-system, to obtain simultaneous hyperspectral and positional imagery at 30Hz frame rate, and application of spectral segmentation techniques to isolate and track the human subject in a cluttered urban scene.

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Fusion of novel biometrics for human tracking and identification

Fusion of novel biometrics for human tracking and identifica...

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2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Jo Nothard John Hargreaves Dan Pearce Chris Harvey Michela Goffredo Mark Nixon John Carter The Institution ofEngineering and Technology QinetiQ Stevenage UK The Institution ofEngineering and Technology University of Southampton Stevenage UK

QinetiQ and Southampton University are engaged in a programme on fusion of novel biometrics for real-world secure environments. The main objective is to develop a camera system for measuring and fusing two key biometrics: gait and hyperspectral signature; for use outdoors, at a distance and in real world scenarios. It will provide a capability to automatically track and identify key individuals remotely and covertly by 3-D analysis of their gait and their spectral signature. This offers a significant tactical advantage over current biometrics systems which either require a cooperative subject or are unreliable in real world scenarios. The programme to date has concentrated upon the core technologies prior to incorporation into a single biometric system and fusion of the respective characteristics. Achievements so far include verification of techniques for 3D gait reconstruction from a single camera, trials of a 16 band IRIS (image replicating imaging spectrometer) camera subsystem, to obtain simultaneous hyperspectral and positional imagery at 30 Hz frame rate, and application of spectral segmentation techniques to isolate and track the human subject in a cluttered urban scene.

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Using ship tracking methods to assist in quality controlling and bias adjusting meteorological observations in a marine environment

Using ship tracking methods to assist in quality controlling...

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IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Hill, J.G.T. Maskell, S.R. Cole, M. Rutherford Appleton Laboratory United Kingdom QinetiQ United Kingdom

ISBN: (纸本)9780863419102

How global temperature has changed in the past is essential to both our understanding of the current climate and our ability to predict future change. The Marine Air Temperature (MAT) record that is derived from the International Comprehensive Ocean Atmosphere DataSet (ICOADS) provides a measure of global temperature which extends back to the mid 19th Century. Although the Sea Surface Temperature record has a greater spatial coverage in the latter parts of the record the MAT record potentially has a lower bias and is an independent record of changes in global temperature. In records prior to the early and mid 19th Century (data yet to be included in ICOADS) MAT becomes the dominant record type with measurements stretching back to the late 18th Century. However, the MAT record faces two substantial issues;firstly the daytime measurements (which become dominant in the early part of the record) are contaminated by solar heating, secondly a large number of the observations in the ICOADS (90% in 1970) have no ship identity. In order to devise corrections for the daytime MAT, it is necessary to be able to differentiate between ship voyages (if not between the ships themselves). Since this has not been considered possible, current MAT datasets (i.e. MOHMAT43N) do not use daytime data except from observations with complete metadata. To create the bias adjustments, we must first identify the individual voyages using their kinematic properties. To do this we have employed a state-of-the-art tracking methodology to break up the mass of unidentified marine observations into ship tracks. This method also has the benefit of being able to differentiate between observing platforms based on the pattern of movement. Here we will present a test case of June 1998 demonstrating some of the potentially available improvements to the MAT record and hence to our understanding of changes in global temperature. © The Institution of Engineering and Technology.

关键词： Climate change

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Using ship tracking methods to assist in quality controlling and bias adjusting meteorological observations in a marine environment

Using ship tracking methods to assist in quality controlling...

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2008 IET seminar on target tracking and Data Fusion: algorithms and applications

作者： Julian G. T. Hill Simon R. Maskell Matthew Cole The Institution ofEngineering and Technology Rutherford and Appleton Laboratory Stevenage Hertfordshire UK The Institution ofEngineering and Technology QinetiQ Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

How global temperature has changed in the past is essential to both our understanding of the current climate and our ability to predict future change. The marine air temperature (MAT) record that is derived from the International Comprehensive Ocean Atmosphere DataSet (ICOADS) provides a measure of global temperature which extends back to the mid 19 Century. Although the sea surface temperature record has a greater spatial coverage in the latter parts of the record the MAT record potentially has a lower bias and is an independent record of changes in global temperature. In records prior to the early and mid 19* Century (data yet to be included in ICOADS) MAT becomes the dominant record type with measurements stretching back to the late 18 Century. However, the MAT record faces two substantial issues; firstly the daytime measurements (which become dominant in the early part of the record) are contaminated by solar heating, secondly a large number of the observations in the ICOADS (90% in 1970) have no ship identity. In order to devise corrections for the daytime MAT, it is necessary to be able to differentiate between ship voyages (if not between the ships themselves). Since this has not been considered possible, current MAT datasets (i.e. MOHMAT43N) do not use daytime data except from observations with complete metadata. To create the bias adjustments, we must first identify the individual voyages using their kinematic properties. To do this we have employed a state-of-the-art tracking methodology to break up the mass of unidentified marine observations into ship tracks. This method also has the benefit of being able to differentiate between observing platforms based on the pattern of movement. Here we will present a test case of June 1998 demonstrating some of the potentially available improvements to the MAT record and hence to our understanding of changes in global temperature.

关键词： Climate change Marine Air temperature Environmental Temperature methylallyl trisulfide air temperature marine DVD Audio Ships climate change bias adjustment meteorological observations Bias CASING INSPECTION sublittoral zone indium

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Derivative-free filters for target motion analysis with bearings-only measurement

Derivative-free filters for target motion analysis with bear...

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IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007

作者： Srinivasan, M. Raj, H. Anitha Haritha, D. Krishna, D. Siva Tyagi, Manoj Kumar Electronics and Computer Engineering Department Computer Science and Engineering Department Koneru Lakshmaiah College of Engineering Vaddeswaram India

ISBN: (纸本)9780863419379

Nonlinear filtering for state and parameter estimation in both defence and civil applications has been recently advanced to accurate, computationally efficient and stable alternatives. The conventional nonlinear estimation technique is the extended Kalman filters (EKF) that uses first order derivative. For chancy and practical applications, the EKF may lead to inaccurate and unstable. In nineties, derivativefree filters such as the central difference filter (CDF) and the unscented Kalman filters (UKF) has been developed to provide accurate and stable estimation. The CDF algorithm for posterior state estimation has been presented in literature [7]. Main contribution of this paper is formulation of the CDF algorithm for prior state estimation and applied that to tracking problem. In this work, target Motion Analysis (TMA) using angle or bearings-only measurement has been studied with both prior and posterior state estimation. The considered tracking problem is highly nonlinear and has uncertainty in initial conditions. Particular focus in this work is to assess the robustness of the CDF in comparison with other nonlinear filters. The frequency of track-loss due to initial condition uncertainty has been studied. The robustness of CDF algorithm is studied with both prior and posterior estimation approach. First, the EKF, UKF and CDF algorithms for posterior estimation are applied to examine the tracking performance. Relative merits of the CDF vis-à-vis EKF and UKF are explored. Secondly, the EKF and CDF algorithm for prior estimation are applied for TMA. With large Monte Carlo simulation runs the tracking performance of EKF and CDF are compared by studying the root mean square error (RMSE) and robustness against initial uncertainty. As the tracking performance of CDF is superior to the EKF and close to the UKF and the computational efficiency of CDF is very close to the EKF, the CDF is one of the candidate for TMA with bearings-only measurement.

关键词： Extended Kalman filters

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The ieeE seminar on target tracking: algorithms and applications

The IEEE Seminar on Target Tracking: Algorithms and Applicat...

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The iee seminar on target tracking: algorithms and applications 2006 (Ref. No. 2006/11359)

The following topics are dealt with: distributed air target tracking; particle filtering; data association; Viterbi algorithm; Riccati equation; infrared image sequences; multiple object tracking and video sequence.

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