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

共 1721 条记录，以下是1491-1500 订阅

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RECOGNITION OF MOVING VEHICLES USING DIRECTIONAL-TEMPORAL PLANE TRANSFORM

RECOGNITION OF MOVING VEHICLES USING DIRECTIONAL-TEMPORAL PL...

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CONF ON INTELLIGENT ROBOTS AND COMPUTER VISION 10 : algorithms AND TECHNIQUES

作者： TANIGUCHI, H FURUSAWA, H SEKI, A IKEBATA, S Mitsubishi Electric Corp. (Japan)

ISBN: (纸本)0819407445

Traffic flow measurement systems, which recognize vehicles and measure traffic parameters by image processing, are researched. We propose a new recognition method for moving vehicles using directional-temporal plane transform (DTT) for the system. DTT is a transformation from spatiotemporal data to 2-D data onto a directional-temporal plane. The transformation is done by projecting feature data of vehicles to a directional axis which is roughly parallel to the moving loci, and by placing the projected data stream side by side in temporal order. We also show an effective extraction algorithm of vehicles from the 2-D data obtained by DTT. Experimental results using real images demonstrate the effectiveness of this method.

关键词： Image processing detection and tracking algorithms Robot vision Robots Machine vision Computer vision technology Cameras Edge detection Magnetic sensors Roads

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ANALYSIS OF IMAGE REGISTRATION algorithms FOR INFRARED IMAGES

ANALYSIS OF IMAGE REGISTRATION ALGORITHMS FOR INFRARED IMAGE...

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CONF ON SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION

作者： VENKATESWARLU, R CHATTERJEE, BN Defence Research and Development Organisation (India) Indian Institute of Technology/Kharagpur (India)

ISBN: (纸本)0819408646

Image registration techniques have gained importance for many applications such as area correlation tracking, handing over recognized target scenes from one sensor to another sensor, tracking an area of interest before detection, tracking point targets, and the latest being multi- target handling capability for defense needs, scene stabilization, etc. No single image registration algorithm (IRA) can work satisfactorily for all applications and in all environments. This paper analyzes the suitability of image registration algorithms for infrared images. Infrared images are characterized by low contrast and sensor nonuniformities such as offset-errors, gain variations resulting in fixed pattern noise (FPN). Particularly, in focal plane arrays (FPA), the output of each detector is characterized by `ax + b' where `a' and `b' are gain and dc offset terms respectively, and `x' is photon flux level falling on the detectors. These parameters and especially their variations from detector element to detector element effect the performance of image registrations algorithms. In this paper, the basic IRAs are analyzed in this context of infrared images with low contrast and FPN. Simulated results using real world images are presented. Novel and inexpensive confidence and redundancy measures have been proposed to improve the performance by detecting misregistrations.

关键词： Image registration Sensors Signal to noise ratio Simulation of CCA and DLA aggregates Infrared imaging Infrared radiation Staring arrays detection and tracking algorithms Curium Image sensors

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DESIGN AND EVALUATION OF MULTIPLE HYPOTHESIS tracking FOR INFRARED SURVEILLANCE SYSTEMS

DESIGN AND EVALUATION OF MULTIPLE HYPOTHESIS TRACKING FOR IN...

引用

4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： BLACKMAN, S DEMPSTER, R BROIDA, T Hughes Aircraft Co. (United States)

ISBN: (纸本)0819408638

This paper describes an overall methodology for the application of a multiple hypothesis tracking (MHT) algorithm to the IR surveillance system problem of tracking dim targets in a heavy clutter or false alarm background. First, It discusses the manner in which the detection and tracking systems are jointly designed to optimize performance. Next, it presents approximate methods that can conveniently be used for preliminary system design and performance prediction. Finally, it discusses the use of a detailed Monte Carlo simulation for final system evaluation and presents results illustrating the proposed methods and comparing predicted and simulation performance.

关键词： Monte Carlo methods Signal processing Infrared imaging Signal to noise ratio Surveillance systems Data processing Target detection Infrared search and track detection and tracking algorithms Infrared sensors

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EVALUATION OF TACTICAL DECISION AID CODE PREDICTIONS OF FLIR RANGE PERFORMANCE

EVALUATION OF TACTICAL DECISION AID CODE PREDICTIONS OF FLIR...

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CONF ON CHARACTERIZATION PROPAGATION, SIMULATION OF SOURCES AND BACKGROUNDS 2

作者： COOPER, AW WALKER, PL MILNE, EA COOK, BJ Naval Postgraduate School (United States) Naval Research Lab. (United States)

ISBN: (纸本)0819408522

Tactical Decision Aid codes provide field prediction of maximum range of FLIR use using simplified local environmental parameter input. A series of experimental comparisons at sea using airborne operational FLIRs with an instrumented ship target have shown poor correlation of observed range with prediction for detection and recognition. Classification and recognition range in UFLR are found to be highly insensitive to radiosonde atmospheric profile data input. Previous work has addressed modeling of the average target to background contrast temperature difference and atmospheric propagation of contrast. This paper addresses the implementation of the MDTD and MRTD algorithms in the code. Comparisons are presented of the prediction accuracy of the UFLR TDA using the standard Moser/Hepfer algorithm and an adaptation of the Johnson criterion used in the NVEOL Ratches code. For the limited data set of the study a reduction of RMS prediction error is achieved using the NVEOL algorithm.

关键词： Target detection Forward looking infrared Atmospheric modeling detection and tracking algorithms Target recognition Data modeling Oceanography Atmospheric propagation Minimum resolvable temperature difference Submerged target modeling

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DEMONSTRATION OF CLUTTER REDUCTION AND AIRCRAFT detection IN MULTISPECTRAL DATA

DEMONSTRATION OF CLUTTER REDUCTION AND AIRCRAFT DETECTION IN...

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4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： HOFF, LE WINTER, EM Naval Ocean Systems Ctr. (United States) Technical Research Associates Inc. (United States)

ISBN: (纸本)0819408638

The DARPA multi-spectral infrared camera (MUSIC) was used for a series of experiments in Australia and Maui, Hawaii in 1991. The Maui experiments, conducted from a high mountain, concentrated on the detection of aircraft. The detection of air vehicles without the use of temporal motion (such as the case of a head-on approaching air vehicle) is a challenging problem when background clutter is present. The technique investigated was not dependent upon either the angular motion or the spectral signature of the aircraft. This approach exploits the differential transmission of the atmosphere in neighboring long wave infrared bands. This differential transmission between the target and background `colors' the background relative to the target and allows its removal. This technique was demonstrated on many examples of MUSIC data collected in Maui, Hawaii. Targets approaching the sensor head-on were successfully detected against clouds and other backgrounds using spectral along with spatial techniques. Several different algorithms were investigated and results are compared.

关键词： Sensors Clouds Target detection detection and tracking algorithms Calibration Infrared radiation Signal processing Long wavelength infrared Signal to noise ratio Optical filters

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INDUCTIVE LEARNING USING GENERALIZED DISTANCE MEASURES

INDUCTIVE LEARNING USING GENERALIZED DISTANCE MEASURES

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CONF ON ADAPTIVE AND LEARNING SYSTEMS

作者： HONAVAR, V Iowa State Univ. (United States)

ISBN: (纸本)0819408719

This paper briefly reviews the two currently dominant paradigms in machine learning--the connectionist network (CN) models and symbol processing (SP) systems; argues for the centrality of knowledge representation frameworks in learning; examines a range of representations in increasing order of complexity and measures of similarity or distance that are appropriate for each of them; introduces the notion of a generalized distance measure (GDM) and presents a class of GDM-based inductive learning algorithms (GDML). GDML are motivated by the need for an integration of symbol processing (SP) and connectionist network (CN) approaches to machine learning. GDM offer a natural generalization of the notion of distance or measure of mismatch used in a variety of pattern recognition techniques (e.g., k-nearest neighbor classifiers, neural networks using radial basis functions, and so on) to a range of structured representations such strings, trees, pyramids, association nets, conceptual graphs, etc. which include those used in computer vision and syntactic approaches to pattern recognition. GDML are a natural extension of generative or constructive learning algorithms for neural networks that enable an adaptive and parsimonious determination of the network topology as well as the desired weights as a function of learning Applications of GDML include tasks such as planning, concept learning, and 2- and 3-dimensional object recognition. GDML offer a basis for a natural integration of SP and CN approaches to the construction of intelligent systems that perceive, learn, and act.

关键词： Distance measurement Surface plasmons Machine learning detection and tracking algorithms Intelligence systems Evolutionary algorithms Object recognition Pattern recognition Algorithm development Neural networks

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FEATURE-EXTRACTION USING MORPHOLOGICAL ANALYSIS OF MULTIRESOLUTION GRAY-SCALE IMAGES

FEATURE-EXTRACTION USING MORPHOLOGICAL ANALYSIS OF MULTIRESO...

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CONF ON SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION

作者： TAMBURINO, LA RIZKI, MM ZMUDA, MA Air Force Wright Lab. (United States) Wright State Univ. (United States)

ISBN: (纸本)0819408646

In this paper, we discuss an initial effort to generate pattern recognizers using a multi- resolution Gabor stack of filtered images and a simple evolutionary search algorithm. The generated feature detectors are sets of pixel detectors that measure intensities and pass these values as feature vectors to neural net classifiers. We demonstrate the use of random search to solve a discrimination problem in which tank images are separated from other military vehicle images. The techniques and results used in this paper for discrimination of grey-scale images are reminiscent of similar approaches used to generate pattern recognizers for binary images. A sparse sampling of the Gabor image stack, using only 35 pixel detectors, produces feature vectors which are readily separated by linear perceptrons.

关键词： Sensors Neural networks Feature extraction Binary data detection and tracking algorithms Image resolution Evolutionary algorithms Image filtering Fourier transforms Morphological analysis

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FEEDFORWARD NEURAL NETS AND ONE-DIMENSIONAL REPRESENTATION

FEEDFORWARD NEURAL NETS AND ONE-DIMENSIONAL REPRESENTATION

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： DIXON, LCW MILLS, DJ Hatfield Polytechnic (United Kingdom)

ISBN: (纸本)0819408751

Feedforward nets can be trained to represent any continuous function, and training is equivalent to solving a nonlinear optimization problem. Unfortunately, it frequently leads to an error function with a Hessian matrix that is effectively singular at the solution. Traditional quadratic based optimization algorithms do not perform superlinearly on functions with a singular Hessian, but results on univariate functions show that even so they are more efficient and reliable than backpropagation. A feedforward net is used to represent a superposition of its own sigmoid activation function. The results identify some conditions for which the Hessian of the error function is effectively singular.

关键词： Artificial neural networks Neural networks Superposition Algorithm development Data hiding Brain Complex systems detection and tracking algorithms Neurons Tolerancing

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CONTRAST PIXEL ENHANCEMENT AND MATCHING IN AN IMAGE SEQUENCE BY RELAXATION 6

CONTRAST PIXEL ENHANCEMENT AND MATCHING IN AN IMAGE SEQUENCE...

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CONF ON MOBILE ROBOTS 6

作者： TU, XW DUBUISSON, B Compiegne Univ. (France)

ISBN: (纸本)081940750X

How to extract a set of significant pixels in an image in order to represent the visual information, and to eventually derive 3-D information about the scene, is the subject of this paper. First we describe a relaxation method to detect contrast points in images, and then we propose an approach of maximum pattern resemblance based on the characteristics of these points to find point matches between pairs of images as well as the matches among images in a sequence. After a few iterations of the detection process, a `stable' pattern of discrete points is obtained and `good' corresponding points are then clustered successfully.

关键词： 3D image processing Image contrast enhancement Image enhancement Information visualization Mobile robots detection and tracking algorithms Digital imaging Image analysis Image processing Visualization

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SELF-GROWING NEURAL NETWORK ARCHITECTURE USING CRISP AND FUZZY ENTROPY

SELF-GROWING NEURAL NETWORK ARCHITECTURE USING CRISP AND FUZ...

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： CIOS, KJ NASA Lewis Research Ctr. and Ohio Aerospace Institute (United States)

ISBN: (纸本)0819408751

The paper briefly describes the self-growing neural network algorithm, CID3, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results for a real-life recognition problem of distinguishing defects in a glass ribbon, and for a benchmark problem of telling two spirals apart are shown and discussed.

关键词： Neural networks Evolutionary algorithms detection and tracking algorithms Fuzzy logic Glasses Machine learning Network architectures Artificial neural networks Data hiding Tin

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