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

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Capaciflector sensor imaging and ranging applications for robot control

Capaciflector sensor imaging and ranging applications for ro...

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Telemanipulator Technology and Space Telerobotics

作者： Kizhner, Semion NASA Goddard Space Flight Ctr. (United States)

ISBN: (纸本)0819413224

One basic robotics task is to position a robot tool point over the geometric center of a symmetric object. This paper presents a fully autonomous control command development technique of linear complexity that solves the robot tool point centering and alignment problem. It is based on non-visual sensor imaging and starts with only a partial image of the target in its field of view. A new capacitive proximity and imaging sensor, called a capaciflector, is being used to obtain 2D discrete images of objects with moderate surface complexity. Considered are spacecraft parts whose imaged surfaces are flat with a simple geometrical shape such as a solid rectangle or a circle.

关键词： Sensors Calibration Image sensors Optical sensors Robotics Image processing Data centers detection and tracking algorithms Ranging Solids

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SINGLE-SCAN tracking USING N INFRARED-SENSORS

SINGLE-SCAN TRACKING USING N INFRARED-SENSORS

引用

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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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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AMBIGUITIES IN EVALUATING PERFORMANCE OF MULTIPLE TARGET tracking algorithms

AMBIGUITIES IN EVALUATING PERFORMANCE OF MULTIPLE TARGET TRA...

引用

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

作者： DRUMMOND, OE FRIDLING, BE General Dynamics Corp. (United States) Institute for Defense Analyses (United States)

ISBN: (纸本)0819408638

Evaluating performance of tracking algorithms is straightforward for a simulation with a single target and one computed track. Performance evaluation with multiple targets, on the other hand, is complex due to ambiguities that create confusion about which target goes with a track. The ambiguities are caused by misassociations or unresolved closely spaced objects. Various considerations in choosing a methodology for performance evaluation to handle these ambiguities are discussed. An approach to assigning tracks to targets is described that takes these considerations into account.

关键词： detection and tracking algorithms Signal processing Sensors Computer simulations Monte Carlo methods Data processing Distance measurement Error analysis Electromagnetic simulation Environmental sensing

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ASSESSING THE PERFORMANCE OF MULTISENSOR FUSION SYSTEMS

ASSESSING THE PERFORMANCE OF MULTISENSOR FUSION SYSTEMS

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SENSOR FUSION CONF : CONTROL PARADIGMS AND DATA STRUCTURES

作者： LLINAS, J Calspan Corp. (United States)

ISBN: (纸本)0819407488

In recent years, numerous prototypical systems have been developed for multisensor data fusion. A typical data fusion process operates on sensor parametric data (e.g., data related to target position or attribute data) in order to develop an order of battle, provide an evaluation of tactical situations, or assess tactical threats. This model, developed by the Data Fusion Sub- panel (DFS) of the Joint Directors of Laboratories, partitions fusion processing into four conceptual levels. Ancillary functions in a fusion system include the human computer interface, data base management, source-preprocessing functions, and communications. Military applications for data fusion span a broad range including fusion of data on board a single platform for identifying other platforms (e.g., identification--friend or foe--neutral systems), threat warning systems, situation assessment, and threat assessment systems. Large scale systems such as the All-Source Analysis System (ASAS) or the Joint Surveillance, Targeting, and Reconnaissance System (JSTARS) provide for direction, coordination, and fusion of both ground-based and airborne sensors to aid in the effective management of a ground based battlefield environment. Such systems have become ever more sophisticated. Indeed, many of the prototypical systems utilize advanced identification techniques such as knowledge-based or expert systems. Dempster-Shafer interface techniques, adaptive neural networks, and sophisticated tracking algorithms. While much research is being performed to develop and apply new algorithms and techniques, little work has been performed to determine how well such methods work or to compare alternative methods against a common problem. The issues of system performance and system effectiveness are keys to establishing how well an algorithm, technique, or collection of techniques perform, and then the extent to which these techniques may be used to achieve success on an operational mission.

关键词： Data fusion Sensors Data modeling Telecommunications Sensor fusion detection and tracking algorithms Target detection Data acquisition Computing systems Algorithm development

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VECTOR FIELD INTERPOLATION USING ROBUST STATISTICS 2

VECTOR FIELD INTERPOLATION USING ROBUST STATISTICS

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CONF ON CURVES AND SURFACES IN COMPUTER VISION AND GRAPHICS 2

作者： ZHONG, JL WENG, JY HUANG, TS Univ. of Illinois/Urbana-Champaign (United States)

ISBN: (纸本)081940747X

This paper investigates the problem of interpolating, under physical constraints, 3-D vector fields from sample vectors at irregular positions. This problem arises from analysis of fluid motion, but our results can also be used in such areas as geometric modeling, data approximation, and the analysis of other types of nonrigid motion. The algorithm proposed in this paper combines the generalized multivariate quadratic interpolation and physical constraints into one step to form an over-determined linear equation system. The least squares solution of this system gives the coefficients of interpolation. Since the interpolation is done in one step and is noniterative, it is computationally efficient. We utilize the methods in robust statistics to detect outliers in the sample data so that the result remains stable in the presence of gross errors. Another merit of our scheme is that by incorporating physical constraints into linear equation system, the algorithm takes into account the characteristics of vector field and is much less sensitive to noise. The algorithm is applied to both synthesized and real data representing 3-D fluid vector field. With the application to 3-D fluid flow in mind, we study the applicability of physical constraints in fluid kinematics and analyze the sources of noise from the real data acquisition. A comparison between our algorithm with previous work shows the robustness of our algorithm. The results of interpolating real flow data are presented.

关键词： Error analysis Particles Statistical analysis Computer vision technology Machine vision Computer graphics Visualization detection and tracking algorithms Velocity measurements Velocimetry

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COMBINING LVQ WITH CONTINUOUS DENSITY HIDDEN MARKOV-MODELS IN SPEECH RECOGNITION

COMBINING LVQ WITH CONTINUOUS DENSITY HIDDEN MARKOV-MODELS I...

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CONF ON NEURAL AND STOCHASTIC METHODS IN IMAGE AND SIGNAL PROCESSING

作者： KURIMO, M TORKKOLA, K Helsinki Univ. of Technology (Finland) IDIAP (Switzerland)

ISBN: (纸本)0819409391

We propose the use of self-organizing maps (SOMs) and learning vector quantization (LVQ) as an initialization method for the training of the continuous observation density hidden Markov models (CDHMMs). We apply CDHMMs to model phonemes in the transcription of speech into phoneme sequences. The Baum-Welch maximum likelihood estimation method is very sensitive to the initial parameter values if the observation densities are represented by mixtures of many Gaussian density functions. We suggest the training of CDHMMs to be done in two phases. First the vector quantization methods are applied to find suitable placements for the means of Gaussian density functions to represent the observed training data. The maximum likelihood estimation is then used to find the mixture weights and state transition probabilities and to re-estimate the Gaussians to get the best possible models. The result of initializing the means of distributions by SOMs or LVQ is that good recognition results can be achieved using essentially fewer Baum-Welch iterations than are needed with random initial values. Also, in the segmental K-means algorithm the number of iterations can be remarkably reduced with a suitable initialization. We experiment, furthermore, to enhance the discriminatory power of the phoneme models by adaptively training the state output distributions using the LVQ-algorithm.

关键词： Data modeling Quantization Speech recognition Stochastic processes detection and tracking algorithms Image processing Signal processing Image segmentation Computer science Information science

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VISUAL EXPERIMENTS FOR A SUBJECTIVE-BASED CONDITIONAL-REPLENISHMENT IMAGE-SEQUENCE CODER INCORPORATING TEXTURE FREEZE 3

VISUAL EXPERIMENTS FOR A SUBJECTIVE-BASED CONDITIONAL-REPLEN...

引用

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

作者： PAPATHOMAS, TV MALAH, D Rutgers Univ. (United States) Technion--Israel Institute of Technology (Israel)

ISBN: (纸本)0819408204

We report on psychovisual experiments designed to obtain subjective-based thresholds for a novel conditional-replenishment image-sequence coder. This coder attempts to avoid the replenishment of textured blocks for which no subjective change has occurred from the previous to the current frame. Typically, such blocks give rise to a large difference signal with respect to the corresponding block in the previous image, and hence are coded (replenished) in commonly used coders. We designed and conducted extensive visual experiments to study the response of the human visual system to stimuli that are relevant to the coding algorithm. Three major classes of experiments were conducted with numerous parametric variations for each, in which the observers were asked to discriminate target elements with properties that differed from those of the background: (1) Uniform targets on uniform background of different intensity. (2) Textured targets of varying standard deviation on a uniform background of the same average intensity. (3) Textured targets on a textured background with the same standard deviation, but different average intensity. We report on the results of these experiments and on the improvement in the performance of the coder, as a result of implementing these results in the encoding algorithm.

关键词： Visualization Computer programming Image filtering Human vision and color perception Target detection Standards development Video Image quality detection and tracking algorithms Solids

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SEMIDIFFERENTIAL INVARIANTS - ALGEBRAIC-DIFFERENTIAL HYBRIDS

SEMIDIFFERENTIAL INVARIANTS - ALGEBRAIC-DIFFERENTIAL HYBRIDS

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3RD CONF ON HYBRID IMAGE AND SIGNAL PROCESSING

作者： KEMPENAERS, P VANGOOL, LJ OOSTERLINCK, A Catholic Univ. of Leuven (Belgium)

ISBN: (纸本)0819408670

In the realm of flexible automation, viewpoint independent object recognition will become increasingly important. An algorithm for the recognition of plane shapes under pseudo- perspective projection is presented. The method is based on the comparison of features that remain invariant under 2-D affine transformations. In particular, the work presented is part of the wider framework of semi-differential invariants. It was successfully tested on a database containing 42 objects.

关键词： Databases Image processing Affine motion model Signal processing Data modeling Image segmentation Object recognition detection and tracking algorithms Edge detection Algorithm development

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METHOD TO EXTRACT AND RECOGNIZE TOPOGRAPHIC SYMBOLS FROM CONTOUR MAPS

METHOD TO EXTRACT AND RECOGNIZE TOPOGRAPHIC SYMBOLS FROM CON...

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2ND INTERNATIONAL CONF ON AUTOMATIC OBJECT RECOGNITION

作者： HUANG, QM PAN, SJ ZHANG, TW Harbin Institute of Technology (China)

ISBN: (纸本)0819408654

To extract and recognize topographic symbols from topographic contour maps is a practical problem in the field of pattern recognition. In this paper, we try to put forward an effective method to solve this problem. By using this method, the symbols are first entracted from the topographic contour maps by eliminating the background of the symbols, and then they are recognized by a neural net, the Hamming net. Experimental results show the effectiveness of this method.

关键词： Binary data detection and tracking algorithms Object recognition Image enhancement Neural networks Pattern recognition Logic Computer science Light sources and illumination Ranging

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