A major issue in the field of mobile robotics today is the detection and tracking of moving objects (DATMO) from a moving observer. In dynamic and highly populated environments, this problem presents a complex and com...
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Posterior densities in nonlinear tracking problems can successfully be constructed using particle filtering. The mean of the density is a popular point estimate. However, especially in multi-modal densities it does no...
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ISBN:
(纸本)9780863419102
Posterior densities in nonlinear tracking problems can successfully be constructed using particle filtering. The mean of the density is a popular point estimate. However, especially in multi-modal densities it does not always represent a reasonable estimate. In multi-targettracking the mean can produce a large bias when there is uncertainty about the labelling of the tracks, also referred to as the mixed labelling problem. The particle based Maximum A Posteriori (MAP) point estimator that has been recently developed is applied to this problem. It is shown by means of simulation that it provides a large improvement over the mean estimate.
Scattering of signals from commercial television or radio channels from air and surface targets can be detected by one or more passive receivers. The received signals can be processed to give bistatic range and range ...
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ISBN:
(纸本)9780863419102
Scattering of signals from commercial television or radio channels from air and surface targets can be detected by one or more passive receivers. The received signals can be processed to give bistatic range and range rate measurements on targets. This paper considers trackingalgorithms to convert the measurements to target tracks using data from a demonstration receiver, with emphasis on the problem of track initiation for low SNR targets where there are many false detections. It is shown that it is possible to track targets in this type of environment. Further development and tuning is required to minimise the number of false tracks initiated.
We present an innovative optical flow based algorithm that uses a memory of both target appearance and motion in order to simultaneously segment and track extended targets through complex scenes. A particularly attrac...
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ISBN:
(纸本)9780863419102
We present an innovative optical flow based algorithm that uses a memory of both target appearance and motion in order to simultaneously segment and track extended targets through complex scenes. A particularly attractive feature of this approach is that is assumes little prior knowledge of the scene content (background, clutter etc) and can cope with a variety of target types and numbers. The algorithm will be demonstrated on synthetic and real-world, visual-band imagery.
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 biometr...
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This paper introduces a new methodology to take account of the Doppler blind zone arising, for example, in GMTI tracking. Here, the measurements are suppressed, when the range-rate of the target drops below a specifie...
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ISBN:
(纸本)9780863419102
This paper introduces a new methodology to take account of the Doppler blind zone arising, for example, in GMTI tracking. Here, the measurements are suppressed, when the range-rate of the target drops below a specified threshold. algorithms based on the new methodology are easy to implement, robust to choice of initial distributions and computationally efficient. Simulations have been conducted for a number of scenarios featuring in earlier comparative exercises. The new techniques exhibit a uniform improvement in estimation accuracy, as compared with earlier proposed approximate analytic techniques.
Artificial neural-networks have been widely applied in various aspects of particle-tracking velocimetry. This paper presents an overview of the different applications and gives an insight into how this technology can ...
Artificial neural-networks have been widely applied in various aspects of particle-tracking velocimetry. This paper presents an overview of the different applications and gives an insight into how this technology can be applied to fuel-flow monitoring. The paper presents a method of flow-field estimation based on particle-tracking velocimetry, without the need to solve the correspondence problem. We also present a method of defeating the obscuration problem found in many optical velocimetry schemes.
In this paper, we describe a video tracking application using the dual-tree polar matching algorithm. The models are specified in a probabilistic setting, and a particle filter is used to perform the sequential infere...
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ISBN:
(纸本)9780863419102
In this paper, we describe a video tracking application using the dual-tree polar matching algorithm. The models are specified in a probabilistic setting, and a particle filter is used to perform the sequential inference. Computer simulations demonstrate the ability of the algorithm to track a simulated video moving target in an urban environment with complete and partial occlusions.
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