The problem of estimating motion and structure of a rigid scene from two perspective monocular views is studied. The optimization approach presented is motivated by the following observations of linear algorithms: (1)...
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ISBN:
(纸本)081861952x
The problem of estimating motion and structure of a rigid scene from two perspective monocular views is studied. The optimization approach presented is motivated by the following observations of linear algorithms: (1) for certain types of motion, even pixel-level perturbations (such as digitization noise) may override the information characterized by epipolar constraint;(2) existing linear algorithms do not use the constraints in the essential parameter matrix E in solving for this matrix. The authors present approaches to estimating errors in the optimal solutions, investigate the theoretical lower bounds on the errors in the solutions and compare them with actual errors, and analyze two types of algorithms of optimization: batch and sequential. The analysis and experiments show that, in general, a batch technique performs better than a sequential technique for any nonlinear problems. A recursive batch processing.technique is proposed for nonlinear problems that require recursive estimation.
A knowledge-based approach to the detection, tracking, and classification of ground-based formations of point targets in sequences of digitized forward-looking infrared (FLIR) image sequences is presented. It is extre...
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ISBN:
(纸本)081861952x
A knowledge-based approach to the detection, tracking, and classification of ground-based formations of point targets in sequences of digitized forward-looking infrared (FLIR) image sequences is presented. It is extremely difficult, using only information in the imagery, to achieve a high probability of detection of such point targets, while maintaining a low false-alarm rate, since point targets have few reliable features to distinguish them from small clutter objects. Use of a priori contextual information can improve the performance of an automated system considerably. The present system has two components: a point target detector and tracker (PTD) which processes the image sequences and supplies candidate point targets to the knowledge-based target formation detector for clustering into formations, which are then classified as linear, V, and the like. The system has been implemented in software written in C and Common Lisp and evaluated on a variety of FLIR image sequences. The results indicate that, in all cases, the knowledge base improves system performance over that attained by the PTD alone.
The authors present an iterative algorithm for the recovery of 2-D motion, i.e., an algorithm for the determination of a transformation which maps one image onto another. The local ambiguity in measuring the motion of...
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ISBN:
(纸本)081861952x
The authors present an iterative algorithm for the recovery of 2-D motion, i.e., an algorithm for the determination of a transformation which maps one image onto another. The local ambiguity in measuring the motion of contour segments (called the aperture problem) makes it necessary to rely on measurements along the normal direction. Since the measured normal flow itself does not agree with the actual normal flow, the full flow recovered from this erroneous normal flow possesses substantial error too, and any attempt to recover the 3-D motion from such full flow is doomed to failure. The present method is based on the observation that a polynomial approximation of image flow provides sufficient information for 3-D motion computation. The use of an explicit flow model makes it possible to improve normal flow estimates through an iterative process. The algorithm has been tested on synthetic and simple natural time-varying images. The image flow recovered from this scheme was sufficiently accurate as to be useful in 3-D structure and motion computation.
The authors examine two important problems, estimation of goodness of fit, in modeling binary single-texture images by discrete Markov random fields. A methodology for comparing parameter estimators is proposed and ap...
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ISBN:
(纸本)081861952x
The authors examine two important problems, estimation of goodness of fit, in modeling binary single-texture images by discrete Markov random fields. A methodology for comparing parameter estimators is proposed and applied to evaluate four estimation procedures. The classes of models considered are four-parameter Derin-Elliot models and four-parameter autobinomial models with second-order neighborhoods. A Min-χ2 estimator is proposed and shown to outperform estimators described in the literature. The methodology is based on a hardcore sampling process over the parameter space and a Wilcoxon rank-sum statistic. A static for assessing the goodness of fit between a specific model and an arbitrary texture image is also proposed and used in a Monte Carlo ranking test. The statistic is experimentally validated on synthetic textures. Experiments on natural textures suggest that second-order binary models do not fit natural textures well.
The problem of reinforcing local evidence of edges while suppressing unwanted information in noisy images is considered using a form of relaxation labeling. The methodology is based on parameterizing a continuous set ...
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ISBN:
(纸本)081861952x
The problem of reinforcing local evidence of edges while suppressing unwanted information in noisy images is considered using a form of relaxation labeling. The methodology is based on parameterizing a continuous set of edge orientation labels using a single vector. A sigmoidal thresholding function similar to that used in artificial neural networks to bias neighborhood-influence and insure convergence to meaningful stable states is also utilized. A global optimization function is defined, and a decentralized parallel algorithm is derived that uses a steepest-gradient-descent approach to arrive at the optimal point on the functional surface, corresponding to desirable edge-reinforced and noise-suppressed labelings. In addition, a modification to the functional is presented which incorporates a thinning operation to insure that each edge is marked by only a single-pixel-wide response. Results from several image data sets indicate that the algorithm performs as well as or better than other relaxation labeling methods, and with improved computational efficiency.
Several parallel algorithms and parallel architectures have been developed for partitional clustering. Hierarchical clustering algorithms are also widely used in exploratory pattern analysis and unsupervised learning....
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ISBN:
(纸本)081861952x
Several parallel algorithms and parallel architectures have been developed for partitional clustering. Hierarchical clustering algorithms are also widely used in exploratory pattern analysis and unsupervised learning. The author proposes parallel algorithms on single-instruction/multiple-data (SIMD) machines for hierarchical clustering, which require intensive computation and large memory storage. The machine model includes a parallel memory system and an alignment network, to facilitate parallel access of both pattern matrix and proximity matrix. Since clustering algorithms tend to generate clusters even when applied to random datal clustering-tendency and cluster-validity studies are usually performed. The author proposes a parallel algorithm to compute one type of cluster validity measure global fit of hierarchy for quantitative data. For a problem with N patterns, considering validity study as well as clustering, the number of memory accesses is reduced from O(3) on a sequential machine to O(N2) on an SIMD machine with N processing.elements (PEs). More general algorithms for different numbers of PEs are also given.
An approach to the computation of a representation of objects with a planar and curved faces using discontinuity features in range images is presented. Edge maps are computed from real laser triangulation images using...
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ISBN:
(纸本)081861952x
An approach to the computation of a representation of objects with a planar and curved faces using discontinuity features in range images is presented. Edge maps are computed from real laser triangulation images using local operators and shadow analysis, and then structured into an edge-junction graph embedding and quantitative information. This is achieved by appealing to certain concepts of line-drawing analysis adapted to the three-dimensional nature of range imaging. The edge-oriented method is primarily useful for objects that are well-described by their edges. The main advantage of edge-based descriptions is that no fixed surface primitives are assumed. On the other hand, this scheme can only represent objects without any surface crease edges (such as a sphere) by viewpoint-dependent limb edges. This information may be insufficient for the ensuing high-level task. Thus, a generalization of the description format might include a surface analysis to provide a richer representation.
An efficient method for finding straight lines in edge maps is described. The algorithm is based on a pyramid structure. At the bottom level of the pyramid, short line segments are detected by applying a Hough transfo...
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ISBN:
(纸本)081861952x
An efficient method for finding straight lines in edge maps is described. The algorithm is based on a pyramid structure. At the bottom level of the pyramid, short line segments are detected by applying a Hough transform to small subimages. The algorithm proceeds, bottom up, from this low-level description by grouping line segments within the local neighborhoods into longer lines. Line segments which have local support propagate up the hierarchy and take part in grouping at higher levels. The length of a line determines approximately the level in the pyramid to which it propagates, and a hierarchical description of the line segments in a scene is obtained. The line-segment-grouping process is also based on a Hough transform. The method is quite efficient and has an attractive architecture which is suitable for parallel implementation.
Summary form only given, as follows. A hybrid electronic correlator for patternrecognition is described. Digital imageprocessing.techniques are used on images input into the processor to enhance the performance of t...
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Summary form only given, as follows. A hybrid electronic correlator for patternrecognition is described. Digital imageprocessing.techniques are used on images input into the processor to enhance the performance of the system. The inputs of the system are displayed on a spatial light modulator (SLM). Correlation is performed with a filter using only phase information stored on an additional SLM. The experimental performance of two-dimensional phase-only filtering concepts is compared to theoretical predictions. SLMs for use as phase-only filtering are characterized and modeled for computer simulation from theoretical and experimental data. The result of the characterization is to develop models for computer simulation of optical components for use as display devices and phase-only filters. A testbed has been developed which has the ability to test components used for the input display, filters and output plane of the processor. The testbed is a modular system that can be used to test, evaluate, and make recommendations on where performance can be improved.
Interpolation of X-ray motion pictures of the heart (cineventiculograms of the left ventricle) is complicated by the low contrast of the images and the elastic motion of the heart. Here, the problem of placing the hea...
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ISBN:
(纸本)081861952x
Interpolation of X-ray motion pictures of the heart (cineventiculograms of the left ventricle) is complicated by the low contrast of the images and the elastic motion of the heart. Here, the problem of placing the heart boundary in each frame of the motion sequence is described by a framework for the application of knowledge in the form of diagnostically relevant models of the heart in motion. A blackboard architecture is utilized as a basis for the image interpretation. In this architecture, local features such as edges are grouped to build a complete description of the moving heart;the knowledge is organized in a hierarchy with knowledge sources (KSs) operating on different levels of the hierarchy and opportunistic problem-solving techniques are used to control the order of activation of both data-directed and goal-driven sources. A series of experiments show how the extracted edge points are linked to form boundary fragments, how these overlapping fragments are collected and combined to form a larger fragment with higher confidence, how the models of the left ventricle boundaries are derived, how these fragments are matched against the models, and how the boundary movements are tracked in the image sequence.
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