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Performing high accurate pose estimation has been an attractive research area in the field of computer vision; hence, there are a plenty of algorithms proposed for this purpose. Starting with RGB or gray scale image data, methods utilizing data from 3D sensors, such as Time of Flight (TOF) or laser range finder, and later those based on RGBD data have emerged chronologically. Algorithms that exploit...
Pattern of Life (POL) analysis constitutes a subset of Activity-based Intelligence (ABI) — understanding those complex spatiotemporal contexts within which entities (e.g., cancer cells, people, etc.) move about and interact, normally-but not always- with a type of recognizable regularity. POL analysis methods are particularly important when attempting to detect and track complex behaviors in stochastic...
We compare several belief fusion methods, including the proportional conflict redistribution rules (PCR5 and PCR6) for multiple sources. The PCR fusion of evidence methods have shown improvement over the classical Dempster-Shafer and Bayesian fusion techniques in the presence of conflicting information. The PCR6 rule shows improvement over PCR5 when the number of sources increases. Using Hasse graphical...
In graph-based target tracking, vertices represent measurements and/or tracklets and edges represent allowable associations. Therefore a solution with a set of tracks is simply a vertex-disjoint path cover of the graph. Under certain (path independence) conditions, the tracking problem can be transformed into one of finding the maximum weight vertex-disjoint path cover of a directed acyclic graph,...
In over-the-horizon radars (OTHRs), the target state updates at a fast rate while the ionosphere state (e.g. the ionospheric height) evolves intermittently and all OTHR based tracking methods have the same prerequisite that the virtual ionospheric height, as the key model parameter in estimating the target state, should be obtained either by ionosondes or external sources. However, ionosondes can...
We attack the problem of persistently tracking cooperative people such as children, the elderly or patients by combining passive tracking and active tracking techniques. Passive tracking uses visual signals from surveillance cameras, but vision based people tracking becomes a hard problem in challenging scenarios such as long-term/heavy occlusion, people changing their movement patterns during occlusion,...
In this paper, we present a randomized version of the finite set statistics (FISST) Bayesian recursions for multi-object tracking problems with application to the space situational awareness (SSA) problem. We introduce a hypothesis level derivation of the FISST equations that shows that the multi-object tracking problem may be considered as a finite state space Bayesian filtering problem, albeit with...
The paper presents a dynamic data-driven symbolic approach to construct generative models of causal cross-dependence among different sources of (possibly heterogeneous) measurements. The main objective here is to identify the input-output relationships in the underlying dynamical system using sensory data only. Synchronized pairs of input and output time series are first independently symbolized via...
This paper presents a labeled multi-Bernoulli filter for track-before-detect with a special focus on visual tracking of multiple targets in video. We show that labeled multi-Bernoulli distribution is a conjugate prior for an image likelihood function with a specific separable form. Following a previously formulated likelihood function (with the desirable separable form) using background subtraction,...
This paper proposes a new generic object recognition (GOR) method based on the multiple feature fusion of 2D and 3D SIFT (scale invariant feature transform) descriptors drawn from 2D images and 3D point clouds. We also use trained Support Vector Machine (SVM) classifiers to recognize the objects from the result of the multiple feature fusion. We analyze and evaluate different strategies for making...
Anomaly detection is an important use of the Automatic Identification Systems (AIS), because it offers support to users to evaluate if a vessel is in trouble or causing trouble. For instance, it can be used to detect if a ship is doing something that may cause an accident or if it has changed its route to avoid bad weather condition. In this work, a new method for finding anomalies in the ships' movements...
In this paper, a new single sensor passive emitter localization approach is presented. The use of signal structure information allows TDOA-based localization with a single moving sensor node. A direct position estimation scheme is derived for the single sensor TDOA localization problem. The feasibility of the proposed method is shown in simulations. The position estimation accuracy of the single senor...
This paper presents an estimation procedure for exploiting multipath signal propagation in shallow water to perform passive ranging. The scenario of interest is a pair of sensors receiving an underwater acoustic signal that has arrived via a bounce from the ocean floor. This approach also applies in other situations, for example, to multiple airborne sensors passively receiving emissions from an airborne...
Trajectories are used in many target tracking and other fusion-related applications. In this paper we consider the problem of modeling trajectories as Gaussian processes and learning such models from sets of observed trajectories. We demonstrate that the traditional approach to Gaussian process regression is not suitable when modeling a set of trajectories. Instead we introduce an approach to Gaussian...
A local series expansion of a received signal is proposed for computing direction of arrival (DOA) in sensor arrays. The advantages compared to classical DOA estimation methods include general sensor configurations, ultra-slow sampling, small dimension of the arrays, and that it applies for both narrowband and wideband signals without prior knowledge of the signals. This makes the method well suited...
Nowadays, data volume, distribution, and volatility makes it difficult to apply traditional Data Mining techniques in the search of global patterns in a domain under observation. This is the case of the methods for discovering associations, which typically require a single uniform dataset. To address the scenarios in which satisfying this requirement is not practical or even feasible, we propose a...
A Bayesian filter for rotation groups in 2D and 3D is derived. The prior, propagator, and measurement probability densities are all assumed to be bandlimited functions on SO(2) or SO(3), expressed as a Fourier series on these compact Lie groups. The posterior, which has a higher bandlimit, is computed and then low-pass filtered, resulting in a bandlimited approximation. The benefits and drawbacks...
Sensors and information sources can produce conflicting evidence for various reasons, including errors and deception. When conflicting evidence is received, some sources produce more accurate evidence than others with regard to the ground truth. The reliability of sources can be expressed by assigning a level of trust to each source. In this situation, multiple fusion strategies can be applied: one...
This paper addresses the problem of multi-static doppler-only tracking in doppler blind zone (DBZ). In such a problem, target measurements are suppressed when the rangerate (doppler) drops below a specified threshold in magnitude (the minimum detectable velocity, MDV). Moreover, tracking using doppler-only measurements is not an easy problem due to its weak observability. In order to improve the estimation...
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