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检索条件"主题词=Detection and tracking algorithms"

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Optimal nonlinear filtering for track-before-detect in IR image sequences

Optimal nonlinear filtering for track-before-detect in IR im...

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Conference on Signal and Data Processing of Small Targets 1999

作者： Rozovskii, B Petrov, A Univ So Calif Ctr Appl Math Sci Los Angeles CA 90089 USA

ISBN: (纸本)0819432954

The 3D matched filter proposed by Reed et al.(18) and its generalizations (e.g. banks of assumed velocity filters (BAVF)) provide a powerful processing technique for detecting moving low observable targets. This technique is a centerpiece of various track-before-detect (TBD) systems. However, the 3D matched filter was designed for constant velocity targets and its applicability to more complicated patterns of target dynamics is not obvious. In this paper the 3D matched filter and BAVF are extended to the case of switching multiple models of target dynamics. We demonstrate that the 3D matched filtering can be cast into a general framework of optimal spatio-temporal nonlinear filtering for hidden Markov models. A robust and computationally efficient Bayesian algorithm for detection and tracking of low observable agile targets in Infrared Search and Track (IRST) systems is presented. The proposed algorithm is fully sequential. It facilitates optimal fusion of sensor measurements and prior information regarding possible threats. The algorithm is implemented as an TBD subsystem for IRST, however the general methodology is equally applicable for other imaging sensors (SAR, HRRR, etc.).

关键词： detection and tracking algorithms Nonlinear filtering 3D acquisition Signal to noise ratio 3D modeling Sensors Switching Target detection Infrared search and track Optimal filtering

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detection of oranges from a color image of an orange tree

Detection of oranges from a color image of an orange tree

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Conference on Applications of Digital Image Processing XXII

作者： Weeks, AR Gallagher, A Eriksson, J Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA

ISBN: (纸本)0819432946

The progress of robotic and machine vision technology has increased the demand for sophisticated methods for performing automatic harvesting of fruit. The harvesting of fruit, until recently, has been performed manually and is quite labor intensive. An automatic robot harvesting system that uses machine vision to locate and extract the fruit would free the agricultural industry from the ups and downs of the labor market. The environment in which robotic fruit harvesters must work presents many challenges due to the inherent variability from one location to the next. This paper takes a step towards this goal by outlining a machine vision algorithm that detects and accurately locates oranges from a color image of an orange tree. Previous work in this area has focused on differentiating the orange regions from the rest of the picture and not locating the actual oranges themselves. Failure to locate the oranges, however, leads to a reduced number of successful pick attempts. This paper presents a new approach for orange region segmentation in which the circumference of the individual oranges as well as partially occluded oranges are located. Accurately defining the circumference of each orange allows a robotic harvester to cut the stem of the orange by either scanning the top of the orange with a laser or by directing a robotic arm towards the stem to automatically cut it. A modified version of the K-means algorithm is used to initially segment the oranges from the canopy of the orange tree. Morphological processing is then used to locate occluded oranges and an iterative circle finding algorithm is used to define the circumference of the segmented oranges.

关键词： Image segmentation Image processing algorithms and systems Image filtering Robotics detection and tracking algorithms Binary data Machine vision RGB color model Algorithm development Laser cutting

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Experiments with driving modes for urban robots

Experiments with driving modes for urban robots

引用

Conference on Mobile Robots XIV

作者： Hebert, M MacLachlan, R Chang, P Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)0819434310

In this paper, we describe experiments on semi-autonomous control of a small urban robot. Three driving modes allow semiautonomous control of the robot through video imagery, or by using partial maps of the environment. Performance is analyzed in terms of maximum speed, terrain roughness, environmental conditions, and ease of control. We concentrate the discussion on a driving mode based on visual servoing. In this mode, a template designated in an image is tracked as the robot moves toward the destination designated by the operator. Particular attention is given to the robustness of the tracking with respect to template selection, computational resources, occlusions, and rough motion. The discussion of algorithm performance is based on experiments conducted at Ft. Sam Houston, TX, on Jul. 5-9 1999. In addition to the driving modes themselves, the performance and practicality of an omnidirectional imaging sensor is discussed. In particular, we discuss the typical imaging artifacts due to ambient lighting.

关键词： Robots Cameras detection and tracking algorithms Algorithm development Image processing Visualization Light sources and illumination Robotics Control systems Fourier transforms

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Calibration of the ARL BoomSAR using rigorous scattering models for fiducial targets over ground

Calibration of the ARL BoomSAR using rigorous scattering mod...

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Conference on Radar Sensor Technology IV

作者： Ressler, M Merchant, B Wong, D Nguyen, L Geng, N Carin, L USA Res Lab AMSRL SERU Adelphi MD 20783 USA

ISBN: (纸本)0819431788

The Army Research Laboratory (ARL) synthetic aperture radar (SAR) system is placed atop a boom lift, and therefore the system is termed a "BoomSAR". The UWB character of this system, covering a frequency spectrum from 40-1200 MHz, makes accurate polarimetric calibration a nontrivial matter. The response of the standard trihedral fiducial target is poorly understood at VHF and UHF frequencies, for which the wave interaction with the soil can be an important issue. Here we employ a rigorous method-of-moments (MoM) analysis of UWB scattering from a trihedral reflector over ground. The soil is modeled as a lossy, dispersive half space, accounted for rigorously via the half-space Green's function. The numerical algorithm is used to evaluate the angle-dependent, polarimetric frequency dependence of scattering from a trihedral target, at VHF and UHF frequencies. This comprehensive study of UWB scattering from a trihedral over soil is critical for system calibration.

关键词： Scattering Calibration Free space Synthetic aperture radar Soil science detection and tracking algorithms Polarization Erbium Polarimetry Analytical research

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Scale-angle CWT features: Application in object recognition

Scale-angle CWT features: Application in object recognition

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Conference on Wavelet Applications in Signal and Image Processing VII

作者： Murenzi, R Zhai, WP Namuduri, K Kaplan, L Clark Atlanta Univ Ctr Theoret Studies Phys Sci Atlanta GA 30314 USA

ISBN: (纸本)0819432997

This paper discusses the utility of scale-angle continuous wavelet transform (CWT) features for object classification. Theses features are used as input to two algorithms: character recognition and target recognition in FLIR images. The corresponding recognition algorithm is robust against noise and allows data reduction. A comparative study is made between two types of directional wavelets derived from the Mexican hat wavelet and the usual template matching.

关键词： Wavelets Continuous wavelet transforms detection and tracking algorithms Signal to noise ratio Nonlinear filtering Object recognition Optical character recognition Target recognition Image filtering Image classification

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Application of the Optimal Brain Surgeon pruning strategy to a real-aperture radar detection algorithm

Application of the Optimal Brain Surgeon pruning strategy to...

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Conference on Radar Sensor Technology IV

作者： Ranney, K Khatri, H Alexander, P USA Res Lab AMSRL SERU Adelphi MD 20783 USA

ISBN: (纸本)0819431788

We have applied the Optimal Brain Surgeon (OBS) pruning strategy to a polynomial discriminator in order to reduce the number of coefficients it employs. The polynomial discriminator multiplies various combinations of test features by the respective coefficients and then sums the products to obtain a discriminant that is compared to a threshold. The test features are derived from the radar data associated with the cell under test, while the coefficients are determined a priori by minimizing the mean-squared error (MSE) between the actual and the desired value of the discriminant over the training set. The OBS pruning strategy examines the Hessian matrix of a network's error surface-derived from the training data-to determine which coefficients can be eliminated without adversely affecting the MSE,Besides simplifying the network, such a reduction may also allow for improved network performance when an unseen test data set is input. We present the application of the OBS pruning strategy to reduce the dimensionality of a polynomial discriminator and show that the reduction in dimensionality does not adversely affect performance.

关键词： Sensors Brain Radar Surgery detection and tracking algorithms Chemical elements Information operations Target detection Silicon Sensor performance

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Geometric hashing and object recognition

Geometric hashing and object recognition

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Vision Geometry VIII Conference

作者： Stiller, P Huber, B Texas A&M Univ Inst Sci Computat College Stn TX 77843 USA

ISBN: (纸本)0819432970

We discuss a new geometric hashing method for searching large databases of 2D images (or 3D objects) to match a query built from geometric information presented by a single 3D object (or single 2D image). The goal is to rapidly determine a small subset of the images that potentially contain a view of the given object (or a small set of objects that potentially match the item in the image). Since this must be accomplished independent of the pose of the object, the objects and images, which are characterized by configurations of geometric features such as points, lines and/or conics, must-be treated using a viewpoint invariant formulation. We are therefore forced to characterize these configurations in terms of their 3D and 2D geometric invariants. The crucial relationship between the 3D geometry and its "residual" in 2D is expressible as a correspondence (in the sense of algebraic geometry). Computing a set of generating equations for the ideal of this correspondence gives a complete characterization of the view independent relationships between an object and all of its possible images. Once a set of generators is in hand, it can be used to devise efficient recognition algorithms and to give an efficient geometric hashing scheme. This requires exploiting the form and symmetry of the equations. The result is a multidimensional access scheme whose efficiency we examine. Several potential directions for improving this scheme are also discussed. Finally, in a brief appendix, we discuss an alternative approach to invariants for generalized perspective that replaces the standard invariants by a subvariety of a Grassmannian. The advantage of this is that one can circumvent many annoying general position assumptions and arrive at invariant equations (in the Plucker coordinates) that are more numerically robust in applications.

关键词： 3D image processing Databases 3D modeling Data modeling Object recognition Matrices detection and tracking algorithms Information visualization Systems modeling Visualization

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tracking radar echoes by multiscale correlation: a nowcasting weather radar application

Tracking radar echoes by multiscale correlation: a nowcastin...

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Conference on Image and Signal Processing for Remote Sensing V

作者： Tanelli, S Facheris, L Cuccoli, F Giuli, D Univ Florence Dipartimento Ingn Elettron I-50139 Florence Italy

ISBN: (纸本)0819434663

An algorithm for storm tracking through weather radar data is presented. It relies on the crosscorrelation principle as in TREC (tracking Radar Echoes by Correlation) and derived algorithms. The basic idea is to subdivide the radar maps in Cartesian format in a grid of square boxes and to exploit the so called local translation hypothesis. The motion vector is estimated as the space shift such that corresponding boxes at different times exhibit the maximum correlation coefficient. The discussed technique adopts a multiscale, multiresolution, and partially overlapped box grid which adapts to the radar reflectivity pattern. Multiresolution decomposition is performed through 2D wavelet based filtering. Correlation coefficients are calculated taking into account unreliable data (e.g. due to ground clutter or beam shielding) in order to avoid strong undesired motion estimation biases due to the presence of such stationary features. Data are gathered through a C-band multipolarimetric doppler weather radar. Results show that the technique overcomes some problems highlighted by researchers in previous related studies. Comparison with radial velocity maps shows good correlation values;although they may vary depending on the specific event and on the orographic complexity of the considered area, estimated motion fields are consistent with the shift of the pattern determined through simple visual inspection.

关键词： Radar Motion estimation Wavelets Doppler effect Reflectivity detection and tracking algorithms Spatial resolution Algorithm development Wavelet transforms Optical inspection

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Acoustic target tracking and target identification - Recent results?

Acoustic target tracking and target identification - Recent ...

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Conference on Unattended Ground Sensor Technologies and Applications

作者： Succi, G Pedersen, TK Gampert, R Prado, G SenTech Inc Woburn MA 01801 USA

ISBN: (纸本)0819431877

Ground and air vehicles have distinctive acoustic signatures produced by their engines and/or propulsion mechanism. The structure of these signatures makes them amenable to classification by pattern recognition algorithms. There are substantial challenges in this process. Vehicle signatures are non-stationary by virtue of variations in engine RPM and maneuvers. Field sensors are also exposed to substantial amounts of noise and interference. We discuss the use of neural network techniques coupled with spatial tracking of the targets to carry out the target identification process with a high degree of accuracy. Generic classification is done with respect to the type of engine (number of cylinders) and specific classification is done for certain types of vehicles. This paper will discuss issues of neural network structure and training and ways to improve the reliability of the estimate through the integration of target tracking and classification algorithms.

关键词： Neural networks Acoustics Network architectures Target recognition Sensors Databases detection and tracking algorithms Missiles Pattern recognition Signal attenuation

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Deferred discrimination algorithm (nibbling) for target filter management

Deferred discrimination algorithm (nibbling) for target filt...

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Conference on Signal Processing, Sensor Fusion, and Target Recognition VIII

作者： Caulfield, HJ Johnson, JL Fisk Univ Dept Phys Nashville TN 37208 USA

ISBN: (纸本)081943194X

A new method of classifying objects is presented. Rather than trying to form the classifier in one step or in one training algorithm, it is done in a series of small steps, or nibbles. This leads to an efficient and versatile system that is trained in series with single one-shot examples but applied in parallel, is implemented with single layer perceptrons, yet maintains its fully sequential hierarchical structure. Based on the nibbling algorithm, a basic new method of target reference filter management is described.

关键词： detection and tracking algorithms Optical filters Image filtering Optical correlators Feature extraction Filtering (signal processing) Hybrid optics Missiles Network architectures Signal processing

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