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Special Section Guest Editorial:Perceptually Driven Visual Information Analysis

Journal of Electronic Imaging 2017年第6期25卷

作者： Larabi, Mohamed-Chaker Lee, Sanghoon El Hassouni, Mohammed Morain-Nicolier, Frédéric Jennane, Rachid Université de Poitiers XLIM-SIC UMR 6172 CNRS Boulevard Marie et Pierre Curie BP 30179 Futuroscope86962 France Yonsei University Multidimensional Insight Lab C703 MDI Lab 3rd Engineering Building Seodaemun-gu120-749 Korea Republic of Mohammed v University of Rabat LRIT URAC 29 Laboratory Faculty of Sciences Avenue Ibn Battouta Rabat Morocco Université de Reims CRESTIC 9 rue de Québec Troyes Cedex10026 France Université d'Orléans I3MTO Laboratory 8 rue Léonard de Vinci OrléansF-45072 France

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Integrating Visual Learning Within a Model-based ATR System 26

Integrating Visual Learning Within a Model-based ATR System

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

作者： Carlotto, Mark Nebrich, Mark Gen Dynam Mission Syst Fairfax VA 22033 USA

ISBN: (纸本)9781510609013;9781510609020

Automatic target recognition (ATR) systems, like human photo-interpreters, rely on a variety of visual information for detecting, classifying, and identifying manmade objects in aerial imagery. We describe the integration of a visual learning component into the Image Data Conditioner (IDC) for target/clutter and other visual classification tasks. The component is based on an implementation of a model of the visual cortex developed by Serre, Wolf, and Poggio. Visual learning in an ATR context requires the ability to recognize objects independent of location, scale, and rotation. Our method uses IDC to extract, rotate, and scale image chips at candidate target locations. A bootstrap learning method effectively extends the operation of the classifier beyond the training set and provides a measure of confidence. We show how the classifier can be used to learn other features that are difficult to compute from imagery such as target direction, and to assess the performance of the visual learning process itself.

关键词： Automatic target recognition Image segmentation Data modeling detection and tracking algorithms Image processing Sensors Classification systems Machine learning Machine vision

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PERFORMANCE ASSESSMENT AT THE JEFFERSON PROVING GROUND DEMONSTRATION OF SYSTEMS FOR THE detection AND IDENTIFICATION OF BURIED UNEXPLODED ORDNANCE

PERFORMANCE ASSESSMENT AT THE JEFFERSON PROVING GROUND DEMON...

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Conference on detection Technologies for Mines and Minelike Targets

作者： MULQUEEN, M GEORGE, V ANDREWS, A SPARROW, D DUGAN, R INST DEF ANAL DIV SCI & TECHNOLALEXANDRIAVA 22311

ISBN: (纸本)0819418528

Between August 1993 and December 1994, the Army Environmental Center conducted a congressionally mandated demonstration of systems for the detection, identification, and remediation of unexploded ordance. Two sites were prepared at Jefferson Proving Ground with emplaced inert ordance of known type in recorded locations and orientations to provide ground truth against which demonstrator performance could be evaluated. Uncertainties due to the sensor, as well as surveying errors on the part of the demonstrators, make matching the demonstrator declarations with the emplaced items on a nontrivial exercise. At the same time, an accurate evaluation of system performance requires that this matching be done in a fair and objective fashion. The matching procedure uses a 'critical distance' to determine whether a demonstrator declaration matches an emplaced item and is, therefore, counted as a detection, or does not and is counted as a false alarm. Declarations that are within the critical distance from an emplaced item are candidates for matches, and those outside the critical distance are false alarms. As expected, the number of matches is a function of the choice of critical distance. Therefore, this distance was varied and the probability of detection was determined as a dependent variable in an attempt to separate true detections from random matches of false alarms to undetected baseline items. As a result of this and other tests, we have gained confidence that relative performance rankings are not dependent on an arbitrary choice of cut- off distance and that the evaluation procedure accurately reflects demonstrator performance at the Jefferson Proving Ground demonstration. In general, detection capabilites were lower than 65 percent and most demonstrators reported multiple false alarms per ordnance item detected.

关键词： Target detection detection and tracking algorithms Environmental sensing General packet radio service Sensors Signal to noise ratio Magnetometers Sensor performance Contamination Defense and security

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FUZZY tracking OF MULTIPLE OBJECTS

FUZZY TRACKING OF MULTIPLE OBJECTS

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CONF ON SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION

作者： PERLOVSKY, LI Nichols Research Corp. (United States)

ISBN: (纸本)0819408646

Existing tracking algorithms have difficulties with multiple objects in heavy clutter'. As a number of clutter objects increases, it is becoming increasingly difficult to maintain and especially to initiate tracks. A near optimal algorithm, the Multiple Hypothesis tracking (MHT)2, initiates tracks by considering all possible associations between multiple objects and clutter event on multiple frames. This, however, requires combinatorially large amount of computation, which is difficult to handle even for neural networks, when a number of clutter objects is large. A partial solution to this problem is offered by the Joint Probability Density Association (JPDA) tracking algorithm3, which performs fuzzy associations of objects and tracks, eliminating combinatorial search. However, the JPDA algorithm performs associations only on the last frame using established tracks and is, therefore, unsuitable for track initiation. The problem is becoming even more complicated for imaging, incoherent sensors, when direct measurement of object velocity via the Doppler effect is unavailable. We have applied a previously developed MLANS neural network'5'6 to the problem of tracking multiple objects in heavy clutter. In our approach the MLANS performs a fuzzy classification of all objects in multiple frames into multiple classes of txacks and random clutter. This novel approach to tracking using an optimal classification algorithm results in a dramatic improvement of performance: the MLANS tracking combines advantages of both the JPDA and the MHT, it is capable of track initiation by considering multiple frames, and it eliminates combinatorial search via fuzzy associations.

关键词： detection and tracking algorithms Neural networks Doppler effect Radar Algorithm development Fuzzy logic Sensors Filtering (signal processing) Optical sensors Velocity measurements

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SINGLE-SCAN tracking USING N INFRARED-SENSORS

SINGLE-SCAN TRACKING USING N INFRARED-SENSORS

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

作者： RUDD, JG MARSH, RA IBM/Federal Sector Div. (United States)

ISBN: (纸本)0819408638

The surveillance of very dim IR targets or `fast-burn' targets, or both, is usually assumed to require the use of either staring sensors or scanning sensors with relatively fast revisit rates. The thesis of this paper is that a greater multiplicity of scanning sensors with relatively slow revisit rates often can be used effectively to achieve the required surveillance results. In particular, we describe conditions under which a dim or fast-burn target can be detected and tracked, and accurate tactical parameters can be computed for the target, by using as few as one observation per sensor per target.

关键词： Sensors Satellites Target detection Infrared sensors Algorithm development detection and tracking algorithms Signal processing Data processing Surveillance Error analysis

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COHERENT LASER-RADAR FOR TARGET CLASSIFICATION

COHERENT LASER-RADAR FOR TARGET CLASSIFICATION

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CONF ON SURVEILLANCE TECHNOLOGIES

作者： KRANZ, W Siemens AG (Germany)

ISBN: (纸本)0819405884

This paper describes a method for classifying targets -- especially helicopters -- by evaluating their vibration signatures. The mechanical vibrations of the targets are mainly caused by all movements of engines, turbines, gears, etc. Different types of targets have different vibration spectra which were measured in field trials by an experimental coherent laser radar. The measured signals show the type characteristic vibration signatures. The signatures can be evaluated by mathematic algorithms. Therefore classification of noncooperative targets is feasible.

关键词： LIDAR Frequency modulation Sensors Target detection Modulation Surveillance Mathematics Fermium Library classification systems detection and tracking algorithms

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Eye-position tracking stereoscopic display using image shifting optics

Eye-position tracking stereoscopic display using image shift...

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Conference on Stereoscopic Displays and Applications VII/Complementary Conference - The Engineering Reality of Virtual Reality 1996

作者： Imai, H Imai, M Ogura, Y Kubota, K NEC CORP LTD OPTOELECTR RES LABSMIYAMAE KUKAWASAKIKANAGAWA 216JAPAN

ISBN: (纸本)0819420271

We have developed an eye-position tracking stereoscopic projector which employs image shifting optics. The display allows 3D images to be viewed without special glasses from any position along a lateral axis. Its image shifting device contains a plane parallel glass plate and is installed in a liquid crystal projector. Refraction produced by inclination of the glass plate shifts the optical axis of the projected image. Since the only moving part in the optics is the lightweight glass plate, the response of the image shifting device is both fast and precise enough for interactive 3D-CAD and virtual reality applications. To improve the system's interactive response, we have widened the stereoscopic viewing area by adding a device which causes the image to vibrate laterally. Also we use a new tracking algorithm which reduces the tracking error that would ordinarily be created by delay time. Experimental results confirm the success of these improvements.

关键词： Glasses detection and tracking algorithms Projection systems Eye Liquid crystals Stereoscopic displays Virtual reality 3D displays Magnetic sensors 3D image processing

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Multiview video coding using a multi-state dynamic programming disparity estimation algorithm

Multiview video coding using a multi-state dynamic programmi...

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Conference on Digital Compression Technologies and Systems for Video Communications

作者： Grammalidis, N Strintzis, MG UNIV THESSALONIKI DEPT ELECT & COMP ENGNTHESSALONIKI 54006GREECE

ISBN: (纸本)0819423564

An efficient disparity estimation and occlusion detection and characterization algorithm for multiocular systems is presented. A dynamic programming algorithm, using a multiview matching cost as well as pure gometrical constraints, is used to provide an estimate of the disparity field and to identify occluded areas. An important advantage of this approach is that not only are the occluded points simultaneously detected, but they are also characterized by the number of views where each point is occluded. Specifically, a 'state' map describing the number of matches for each imaged pixel and thus identifying occluded points in the multiview sequence is produced. The disparity and state information is then coded using a directional coding technique and applied to obtain virtual images from intermediate viewpoints. Experimental results, obtained using a four-view image sequence, illustrate the performance of the proposed technique.

关键词： Computer programming detection and tracking algorithms Video coding Imaging systems Panoramic photography Cameras Computer engineering Computing systems Image display Stereoscopy

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BAYESIAN NEURAL-NETWORK ATR FOR MULTIFEATURE SAR

BAYESIAN NEURAL-NETWORK ATR FOR MULTIFEATURE SAR

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Conference on algorithms for Synthetic Aperture Radar Imagery

作者： HILBERT, EE CHANG, CF LORAL DEF SYST ARIZONA LITCHFIELD PKAZ 85340

ISBN: (纸本)0819415340

This paper presents a description of a Bayesian neural network (BNN) automatic target recognition (ATR) algorithm specifically developed to efficiently exploit the correlated relationships between the joint dimensional distribution properties of the multiple features. A multidimensional clustering process is used to define a Parzen estimate which approximates the Bayesian a posteriori decision function, but without limiting constraints regarding multimodal or correlated density function forms in multidimensional feature space. The mathematical derivation is placed in the form of a multilayer neural network, including Kernel function variance adaptation to accommodate small training data sets, and Kernel function tail saturation for robust handling of multidimensional feature data not represented in the training data. The BNN is shown to be a hybrid Bayesian/neural net classifier. It has a robust Bayesian statistical classifier as an initial state, and a feedback learning structure which enables learning corrections localized only to the feature space in the vicinity of the error. In addition, a method is described for integrating scene context information, spatial constraints, and a priori probability information into the BNN classifier. Example uses of the BNN algorithm are discussed for recent programs which obtained multiple feature ATR improvements from using the BNN with multiple frequencies, polarizations, aspect angles, and 3D interferometric SAR features.

关键词： Automatic target recognition Target detection Target recognition detection and tracking algorithms Neural networks Synthetic aperture radar Error analysis Algorithm development Polarization Evolutionary algorithms

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Stylometrics of artwork: uses and limitations

Stylometrics of artwork: uses and limitations

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Conference on Computer Vision and Image Analysis of Art

作者： Hughes, James M. Graham, Daniel J. Rockmore, Daniel N. Dartmouth Coll Dept Comp Sci Hanover NH 03755 USA Dartmouth Coll Dept Math Hanover NH 03755 USA

ISBN: (纸本)9780819479242

A number of digital image analysis techniques have been developed in recent years to address art historical questions. These techniques allow non-destructive analyses of art images that can target outstanding problems of attribution, historical ordering, and other stylistic dimensions. However, great care must be taken in designing the comparisons to which these techniques are applied. In this paper, we review recent work by our lab and by others aimed at establishing a toolbox of stylometrics, and we discuss some of the uses and limitations of these methods. We describe a technique that provides robust classification of authentic drawings by Pieter Bruegel the Elder, and we demonstrate new techniques for art historical analysis applied to the works of other masters. Specifically, we demonstrate the use of two low-level statistics (the slope of the log amplitude spectrum and color histogram correlation) to analyze the works of Picasso and Braque. Finally, we show that face detection and recognition techniques may play a useful role in the attribution of works of art. The rationale for employing vision coding-like methods (e. g., sparse coding) in stylometry is also reviewed. We conclude that generic authentication tools are unlikely to provide reliable stylometric predictions but that with careful construction of comparison sets - which we believe must be done in close collaboration with art historians - these techniques provide important predictions that can be weighed against other art historical evidence. We argue further that concurrent predictions derived from analysis of many independent dimensions of image data (e. g., color, luminance, and spatial statistics) provide the strongest evidence for digital stylometric determinations.

关键词： Facial recognition systems Statistical analysis Image analysis detection and tracking algorithms Analytical research Image compression RGB color model Image filtering Nondestructive evaluation Statistical modeling

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