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

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LINEAR-TIME RECOGNITION OF DIGITAL POLYNOMIAL CURVES AND SURFACES THAT HAVE PERIODIC DIFFERENCES 2

LINEAR-TIME RECOGNITION OF DIGITAL POLYNOMIAL CURVES AND SUR...

引用

Vision Geometry II Conference

作者： VEELAERT, P STATE UNIV GHENT VAKGRP ELISB-9000 GHENTBELGIUM

ISBN: (纸本)0819413259

Digital polynomial curves and surfaces arise from the digitization of algebraic surfaces such as lines, parabolas, planes, or paraboloids. It is known that the n-th difference of a digital polynomial curve of degree n is periodic for polynomials that have rational coefficients. In this paper we consider the following problem: Suppose we have a digital curve S whose n-th difference is known to be periodic. When is S a digital rational polynomial curve? As a solution to this problem we state a simple criterion that can be checked in linear time. As a first application of this criterion we describe a linear time algorithm for the recognition of digital straight lines. In comparison to other algorithms, the advantages of the new algorithm are its simplicity, and its ability to actually find the coefficients of the rational polynomial representing the line. We then go on to discuss the applicability of this criterion to the recognition of digital curves and surfaces of arbitrary degree.

关键词： detection and tracking algorithms Reconstruction algorithms Vision geometry Information operations Algorithm development Astatine Image analysis Image segmentation Pattern recognition Shape analysis

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CAN MACHINE VISION BE HELPED FROM INSIGHTS INTO HUMAN VISION 3

CAN MACHINE VISION BE HELPED FROM INSIGHTS INTO HUMAN VISION

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CONF ON HUMAN VISION, VISUAL PROCESSING, AND DIGITAL DISPLAY 3

作者： PAVLIDIS, T SUNY/Stony Brook (United States)

ISBN: (纸本)0819408204

Machine vision has exhibited rather slow progress over the last 25 years compared to other areas of Computer Technology and an interesting question is whether more progress will be made by continuing intensively the current approaches in research or instead by searching for new directions. I will present a thesis that more research along some of the prevailing lines will lead to best to marginal advances. For example, current edge detectors are very good at finding step edges. The problem is that their major objective, finding object outlines, is not equivalent to step edge finding. It seems that people find object outlines by a process of simultaneous interpretation and low level processing of the image. Such integration should be contrasted to one of the prevailing models in machine vision which assumes a linear sequence of a few distinct processes from low level to high level vision. (When researches talk about 'interpretation guide segmentation' they usually refer to the labeling of already obtained features using high level models of the scene.) If the levels interact strongly, then optimizing the processing techniques for each level separately (for example edge detection for low level vision) is not going to be fruitful. Since human vision is the reason that we believe that machine vision is even possible, a deeper examination of the human or animal vision recognition process is essential to the further progress of machine vision.

关键词： Machine vision Human vision and color perception Sensors Image processing Image segmentation Visual process modeling detection and tracking algorithms Optical character recognition Visualization Edge detection

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Real-time face tracking and pose correction for face recognition using active appearance models

Real-time face tracking and pose correction for face recogni...

引用

Conference on Biometric Technology for Human Identification IV

作者： Heo, Jingu Savvides, Marios Carnegie Mellon Univ ECE Dept Pittsburgh PA 15213 USA

ISBN: (纸本)9780819466617

This paper presents a fully automatic real-time face recognition system from video by using Active Appearance Models (AAM) for fitting and tracking facial fiducial landmarks and warping the non-frontal faces into a frontal pose. By implementing a face detector for locating suitable initialization step of the AAM shape searching and fitting process, new facial images are interpreted and tracked accurately in real time (15fps). Using an Active Appearance Model (AAM) for normalizing facial images under different poses and expressions is crucial to providing improved face recognition performance as most systems degrade matching performance with even smallest pose variation. Furthermore the AAM is a more robust feature registration tracking approach as most systems detect and locate the eyes while AAMs detect and track multiple fiducial points on the face holistically. We show examples of AAM fitting and tracking and pose normalization including an illumination pre-processing step to remove specular and cast shadow illumination artifacts on the face. We show example pose normalization images as well as example matching scores showing the improved performance of this pose correction method.

关键词： Facial recognition systems Image processing Video 3D modeling detection and tracking algorithms Performance modeling Principal component analysis Sensors Automatic tracking Databases

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PROXIMITY CORRECTION OF HIGH DOSED FRAME WITH PROXECCO

PROXIMITY CORRECTION OF HIGH DOSED FRAME WITH PROXECCO

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Conference on Electron-Beam, X-Ray and Ion-Beam Submicrometer Lithographies for Manufacturing IV

作者： EISENMANN, H WAAS, T HARTMANN, H GMBH MUNICHGERMANY

ISBN: (纸本)0819414891

Usefulness of electron beam lithography is strongly related to the efficiency and quality of methods used for proximity correction. This paper addresses the above issue by proposing an extension to the new proximity correction program PROXECCO. The combination of a framing step with PROXECCO produces a pattern with a very high edge accuracy and still allows usage of the fast correction procedure. Making a frame with a higher dose imitates a fine resolution correction where the coarse part is disregarded. So after handling the high resolution effect by means of framing, an additional coarse correction is still needed. Higher doses have a higher contribution to the proximity effect. This additional proximity effect is taken into account with the help of the multi-dose input of PROXECCO. The dose of the frame is variable, depending on the deposited energy coming from backscattering of the proximity. Simulation proves the very high edge accuracy of the applied method.

关键词： Electron beam lithography Backscatter Error analysis Scattering Convolution Deconvolution detection and tracking algorithms Fourier transforms Laser scattering Solid state electronics

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SINGLE LOOK tracking NOISE FOR INTENSITY AND BINARY CENTROIDING algorithms FOR RESOLVED TARGETS AND PERFORMANCE COMPARISON BETWEEN SHARED AND SEPARATE APERTURE ACTIVE tracking

SINGLE LOOK TRACKING NOISE FOR INTENSITY AND BINARY CENTROID...

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

作者： BANDERMANN, L KWONG, R Lockheed Missles & Space Co. Inc. (United States)

ISBN: (纸本)0819408638

Expressions are derived for the single look tracking noise (SLTN) for an unthresholded intensity centroid algorithm and a binary centroid with a lower threshold. The SLTN is defined as the rss value of the rms errors due to (1) photoelectron statistics, (2) background in the tracking gate, and (3) non-coincidence of the object boundaries and the focal plane array (FPA) detector pixels. The expressions, eqs. (27) and (28) below, are applied to typical directed energy weapon scenarios where the objects are pulse-illuminated distant, Lambertian targets. We find for both algorithms that the SLTN decreases with increasing illuminator energy to a terminal value set by the boundary mismatch error (3) above, but for a fixed illumination and pixel footprint on the target this error is smaller for the intensity algorithm. For each algorithm, the footprint can be optimized to obtain a minimal SLTN, and in the cases studied the binary SLTN was consistently lower than the intensity SLTN. Furthermore, the dependence on illuminator pulse energy E is approximately 1/(root)E for the intensity, approximately 1/E^2/3 for the binary centroid. Finally, the SLTN is approximately proportional to 1/D(root)(eta) , where D is the collecting aperture and (eta) is the tracker photon efficiency (transmission X quantum). Thus the advantage of a `shared' DEW tracker compared to `separate' is typically a factor 5 or less.

关键词： Binary data detection and tracking algorithms Error analysis Directed energy weapons Data processing Signal processing Fiber optic illuminators Staring arrays Quantum efficiency Sensors

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ADVANCED INPLANE ROTATION-INVARIANT FILTER RESULTS 14

ADVANCED INPLANE ROTATION-INVARIANT FILTER RESULTS

引用

CONF ON APPLICATIONS OF DIGITAL IMAGE PROCESSING 14

作者： RAVICHANDRAN, G CASASENT, D Carnegie Mellon Univ. (United States)

ISBN: (纸本)0819406953

Advanced filter algorithms using in-plane rotation invariance as an additional constraint during filter synthesis are presented. The new rotation-invariant Minimum Average Correlation Energy (RI-MACE) filter provides sharp, easily detected correlation peaks and excellent discrimination against other false objects. In the presence of background noise and clutter, the rotation-invariant Minimum Noise and Correlation Energy (RI-MINACE) filter (modified RI- MACE filter) uses the noise information during filter synthesis to obtain improved noise performance and also maintain easily detected correlation peaks. New test results are presented to show the improved discrimination capability of the RI-MACE filter and the improved noise performance of the RI-MINACE filter.

关键词： Image filtering detection and tracking algorithms Optical filters Signal to noise ratio Digital image processing Fourier transforms Electronic filtering Interference (communication) Chemical elements Target recognition

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Hyperspectral Sub-Pixel Target Identification using Least-Angle Regression

Hyperspectral Sub-Pixel Target Identification using Least-An...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI

作者： Villeneuve, Pierre V. Boisvert, Alex R. Stocker, Alan D. Space Comp Corp Los Angeles CA 90025 USA

ISBN: (纸本)9780819481597

A novel approach to VNIR hyperspectral target identification is presented based on the Least-Angle Regression (LARS) variable selection and model building algorithm. The problem to be solved is that of accurately identifying a target's primary signature component given a sub-pixel observation. Traditional matched detectors (MF, ACE, etc.) perform well at discriminating a target from a random cluttered background, but do not perform so well at unambiguously matching an observation with its counterpart in a large spectral library containing thousands of signatures. The LARS model-building algorithm efficiently selects a parsimonious subset of a large ensemble of model terms to optimally describe a particular target observation. The LARS solution technique is a recent addition to the family of model selection algorithms that includes Stepwise Regression, Forward Selection, and Backward Elimination. LARS is particularly well-suited to this problem as it is easily modified to enforce material abundance constraints: positive coefficients that sum to unity. Other approaches generally enforce such constraints in an ad-hoc fashion or use computationally demanding nonlinear programming solution techniques. LARS enforces these constraints as an inherent property of the model while remaining as computationally efficient as traditional sequential linear least-squares solvers. We demonstrate and quantify sub-pixel material identification performance using simulated target observations tested against large signature libraries.

关键词： Target detection detection and tracking algorithms RGB color model Target recognition Reflectivity Sensors Hyperspectral target detection Data modeling Digital filtering Feature selection

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ARTIFICIAL NEURAL NETWORKS FOR ACOUSTIC TARGET RECOGNITION

ARTIFICIAL NEURAL NETWORKS FOR ACOUSTIC TARGET RECOGNITION

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1st International Conference on Applications and Science of Artificial Neural Networks

作者： ROBERTSON, JA MOSSING, JC WEBER, B IIT RES INST DAYTONOH 45432

ISBN: (纸本)0819418455

Acoustic sensors can be used to detect, track and identify non-line-of-sight targets passively. Attempts to alter acoustic emissions often result in an undesirable performance degradation. This research project investigates the use of neural networks for differentiating between features extracted from the acoustic signatures of sources. Acoustic data were filtered and digitized using a commercially available analog-digital convertor. The digital data was transformed to the frequency domain for additional processing using the FFT. Narrowband peak detection algorithms were incorporated to select peaks above a user defined SNR. These peaks were then used to generate a set of robust features which relate specifically to target components in varying background conditions. The features were then used as input into a backpropagation neural network. A K-means unsupervised clustering algorithm was used to determine the natural clustering of the observations. Comparisons between a feature set consisting of the normalized amplitudes of the first 250 frequency bins of the power spectrum and a set of 11 harmonically related features were made. Initial results indicate that even though some different target types had a tendency to group in the same clusters, the neural network was able to differentiate the targets. Successful identification of acoustic sources under varying operational conditions with high confidence levels was achieved.

关键词： Neural networks Acoustics detection and tracking algorithms Databases Feature extraction Target recognition Acoustic emission Artificial neural networks Target detection Signal to noise ratio

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ANGULAR-MOMENTUM AND BALLISTIC tracking

ANGULAR-MOMENTUM AND BALLISTIC TRACKING

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

作者： KOLBE, RL Naval Research Lab. (United States)

ISBN: (纸本)0819408638

The correlation and tracking problem for ballistic objects is a major concern for the Strategic Defense Initiative (SDI). In this presentation, the use of angular momentum for gating and assignment of reports and tracks of ballistic objects is proposed. The various errors and appropriate statistical tests that could be used on angular momentum to potentially improve the tracking and correlation, multi-track hypothesis and Kalman filters are studied. The investigation is performed in earth centered inertial Cartesian coordinates for position, velocity, and acceleration in tracking, gating, and assignment. A discussion is given of a brief investigation, the theory developed, the results of numerical test, and the conclusions.

关键词： Error analysis detection and tracking algorithms Filtering (signal processing) Data processing Signal processing Evolutionary algorithms Algorithm development Defense and security Ions Nonlinear filtering

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Model-based detection, Segmentation, and Classification of Compact Objects 24

Model-based Detection, Segmentation, and Classification of C...

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Conference on Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV

作者： Carlotto, Mark J. Gen Dynam Adv Informat Syst Pittsfield MA 01201 USA

ISBN: (纸本)9781628415902

A unified model-based approach to ATR that uses 3D models to control detection, segmentation, and classification is described. Objects are modeled by rectangular boxes whose dimensions are Gaussian random variables. A fast predictor estimates the size and shape of expected objects in the image, which controls detection and segmentation algorithms. Segmentation fits oriented rectangles (length x width @ pose) to object-like regions detected using a multi-level thresholding/region tracking approach. detections are classified by comparing measured to predicted region length and width in the pose direction. The method is fast and requires only a coarse characterization of objects/object classes.

关键词： Image segmentation 3D modeling Optical tracking Systems modeling Binary data Sensors Automatic target recognition Classification systems detection and tracking algorithms Image processing algorithms and systems

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