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In many useful video tracking situations, targets move through repeated mutual occlusions. As targets undergo occlusions, the feature subsets and combinations of those features that are effective in identifying the target and improving tracking performance may change. We use combinatorial fusion analysis to select and evaluate criteria by which to identify the combination of features that will produce...
Tracking ground moving objects using aerial video sensors is very challenging when the objects go through periods of occlusion caused by trees or buildings. If the occlusion interval is relatively large, there are confusing objects in the vicinity, or the object performs abrupt maneuvers while occluded, maintaining continuous tracks after the occlusion requires advanced exploitation of the imagery...
Using suitable topoi of presheaves, a categorical definition of measure is given. When the general definition is specialized to particular categories made of sets of possibility, probability or imprecise probability measures, the internal language of the corresponding topos gives a valid and complete proof system for the corresponding semantics. An application of this method to data fusion in mobile...
The MLPDA is based on maximizing statistical likelihood according to a precise model in which there is no process noise. The PMHT (probabilistic multi-hypothesis tracker) provides an alternative perspective: each contact may be taken as independent and a-priori equally-equipped to be target-generated. Our results indicate that the MLPMHT is the better tracker in multi-static data. A further advantage...
Clustering has been known as a popular technique for pattern recognition, image processing, and data mining. Unfortunately, all known clustering algorithms tend to break down in high dimensional spaces; this is due to the inherent sparsity of the points. We investigate, in this paper, the use of linear and nonlinear principal manifolds for learning low-dimensional representations for clustering. Several...
For pt.I see ibid., p.Z001330-7 (2006). Many estimators and filters provide assessments of their own estimation error. Are these self-assessments trustable? What is the degree to which they are trustable? This is Part II of a two-part series that provides answers to some of these questions, referred to as the credibility of the estimators. It proposes several tests for credibility and a test-based...
This paper reaches beyond the data fusion community to find a novel way to approach the assignment problem in track-to-track (T2T) data fusion. Cluster analysis techniques are explored as a source of assignment algorithms that are practical and efficient. The proposal to apply cluster analysis to the assignment problem is based on a re-examination of the unique requirements of track-to-track fusion...
Data fusion of thermal and visual images is a solution to overcome the drawbacks present in individual thermal and visual images. Data fusion using different approach is discussed and results are presented in this paper. Traditional fusion approaches don't produce useful results for face recognition. An optimized approach for face data fusion is developed which works for face data fusion equally well...
Multiple hypothesis tracking algorithms that rely on hypothesis probabilities for pruning typically generates the n-best global hypotheses. In some cases, the probability mass is diffuse in the space of global hypotheses and a large n is desirable, implying a high computational demand. In this work, we present an alternative method for evaluation of hypothesis probabilities. Global hypotheses are...
Most estimators and filters provide assessments of their own estimation error, often in the form of mean-square error. Are these self- assessments trustable? What is the degree to which they are trustable? This is Part I of a two-part series that provides answers to some of these questions, referred to as the credibility of the estimators. It formulates the concept of credibility, proposes tests for...
The development of an algorithm for fusing an ESM track to multiple radar tracks is presented. This work is motivated by the difficulty of associating ESM sensor data with large measurement errors to closely-spaced radar tracks. The algorithm presents a novel approach to fusing identity information. It assigns to multiple radar tracks the identity information content of an ESM track. The identity...
In this paper we consider the extension of non-monotonic preference logic with the distinction between controllable (or endogenous) and uncontrollable (or exogenous) variables, which can be used for example in agent decision making and deliberation. We assume that the agent is optimistic about its own controllable and pessimistic about its uncontrollable, and we study ways to merge these two distinct...
Higher-level fusion (e.g., level 2 that deals with derivation of relations among objects) often involves symbolic processing of information obtained from lower levels (e.g., level 1, which deals with object detection, identification and tracking) which is based upon quantitative algorithms. The quantitative algorithms pass only some information to higher levels; some of the information is abstracted...
Passive sonar depends on signals of opportunity to detect, track and localize targets. These signals are typically detected and then tracked using Kalman filter-type signal followers. Target motion analysis (TMA) is then used to estimate the target's range and, from this, its position, course and speed. The accuracy of TMA is strongly dependent on the duration of the available track. Initiating a...
This paper describes two scheduling algorithms designed to improve target tracking performance in a distributed network of binary proximity sensors. Tracking with such sensors is a difficult problem as they only transmit a single binary digit regarding the presence of a target. In addition, the operational status of these sensors may not be accurately known. This paper describes extensions to a Gaussian...
This paper describes the integration of a particle filter and a continuous version of the transferable belief model. The output from the particle filter is used as input to the transferable belief model. The transferable belief model's continuous nature allows for the prior knowledge over the classification space to be incorporated within the system. Classification of objects is demonstrated within...
This paper addresses the problem of optimizing the navigation of an intelligent mobile in a real world environment, described by a map. The map is composed of features representing natural landmarks in the environment. The vehicle is equipped with a sensor which allows it to obtain range and bearing measurements from observed landmarks during the execution. These measurements are correlated with the...
This paper describes a real time face detection and tracking system. The method consists in modelling the skin face by a pixel fusion process of three colour sources within the framework of the Demster-Shafer theory. The algorithm is composed of two phases. In a simple and fast initialising stage, the user selects successively in an image, a shadowy, an overexposed and a zone of mean intensity of...
Network-centric multisensor-multitarget tracking has numerous advantages over single-sensor or single-platform tracking. In this paper, we present a solution to one of the main problems of network-centric tracking, namely, decentralized information sharing among the platforms participating in the distributed data fusion. This paper presents a decision mechanism that provides each platform with the...
A key challenge presented by the increasing volume and complexity of information collectable from battlespace situations is the development of intelligent applications able to automatically analyze the information and identify critical enemy activities in a timely manner. What makes this information fusion problem particularly difficult is the strong contextual dependency of the interpretation of...
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