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Linear and incremental acquisition of invariant shape models from image sequences

Linear and incremental acquisition of invariant shape models...

引用

international conference on computer vision (ICCV)

作者： D. Weinshall C. Tomas IBM Thomas J. Watson Research Center Hawthorne NY USA

the authors show how to automatically acquire similarity-invariant shape representations of objects from noisy image sequences under a weak perspective. the incremental nature of the method makes it possible to process images one at a time, moving away from the storage-intensive batch methods of the past. It is based on the observation that the trajectories that points on the object form in weak-perspective image sequences are linear combinations of three of the trajectories themselves, and that the coefficients of the linear combinations represent shape in an affine-invariant basis. A nonlinear but numerically sound preprocessing state is added to improve the accuracy of the results even further. Experiments showed that attention to noise and computational techniques improved the shape results substantially with respect to previous methods.< >

关键词： Shape image sequences image recognition Acoustic noise Noise shaping Cameras computer science image storage Rivers Libraries

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Silhouette-based object recognition through curvature scale space

Silhouette-based object recognition through curvature scale ...

引用

international conference on computer vision (ICCV)

作者： F. Mokhatarian H. Murase NTT Basic Res. Lab. Tokyo Japan NTT Basic Research Laboratories Japan

A complete and practical isolated-object recognition system has been developed which is very robust with respect to scale, position and orientation changes of the objects as well as noise and local deformations of shape due to perspective projection, segmentation errors and non-rigid material used in some objects. the system has been tested on a wide variety of 3-D objects with different shapes and surface properties. A light-box setup is used to obtain silhouette images which are segmented to obtain the physical boundaries of the objects which are classified as either convex or concave. Convex curves are recognized using their four high-scale curvature extrema points. Curvature scale space (CSS) representations are computed for concave curves. the CSS representation is a multi-scale organization of the natural invariant features of a curve. A three-stage coarse-to-fine matching algorithm quickly detects the correct object in each case.< >

关键词： Object recognition Shape image segmentation Cascading style sheets Noise shaping Machine vision image recognition Cameras Laboratories Noise robustness

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Inversion of convolution by small kernels 5th

Inversion of convolution by small kernels

引用

5th international conference on computer Analysis of images and patterns, CAIP 1993

作者： Suesse, H. Voss, K. Friedrich-Schiller-University Jena Department of Mathematics and Informatik Digital Image Processing Group Jena6900 Germany

ISBN: (纸本)9783540572336

Discrete convolution is a very important operation for filter design, image restoration, and applications [4,8, 10,11,16].In this paper, we investigate the existence of inverse elements in respect to convolution, and we derive a method to compute inverse elements without using Fourier transform. Furthermore, we get a simple condition for existence of inverse elements which is easy to verify. We describe the computation of small convolution kernels. these small convolution kernels are least squares optimal [15]. By a simple idea, we can regularize the problem, and the computational effort can be reduced drastically. Furthermore, we can use this theory to restore noise pictures, and we can develop a regularization theory. For the clarity of presentation, the approach given here is one-dimensional, but the multidimensional generalization is straightforward. © 1993, Springer Verlag. All rights reserved.

关键词： Convolution

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Fast and robust 3D recognition by alignment

Fast and robust 3D recognition by alignment

引用

international conference on computer vision (ICCV)

作者： T.D. Alter W.E.L. Grimson Department of EECS M. I. T. A. I. Laboratory Cambridge MA USA

Alignment is a common approach for recognizing 3-D objects in 2-D images. Current implementations handle image uncertainty in ad hoc ways. these errors, however, can propagate and magnify through the alignment computations, such that the ad hoc approaches may not work. the authors give a technique for tightly bounding the propagated error, which can be used to make the recognition robust while still being efficient. Previous analyses of alignment have demonstrated a sensitivity to false positives. But these analyses applied only to point features, whereas alignment systems often rely on extended features for verifying the presence of a model in the image. A new formula is derived for the selectivity of a line feature. It is experimentally demonstrated using the technique for computing error bounds that the use of line segments significantly reduces the expected false positive rate. the extent of the improvement is that an alignment system that correctly handles propagated error is expected to remain reliable even in substantially cluttered scenes.< >

关键词： Robustness Uncertainty Contracts Predictive models image recognition image analysis Layout Artificial intelligence image segmentation Object recognition

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Discrete models for energy-minimizing segmentation

Discrete models for energy-minimizing segmentation

引用

international conference on computer vision (ICCV)

作者： A. Ackah-Miezan A. Gagalowicz INRIA Rocquencourt Le Chesnay France

the image segmentation problem may be considered as the search for a way to subdivide an image domain into regions which represent the projection of visible parts of objects in a real scene. the authors analyze the problem of image segmentation in the framework of the approximation theory as defined by D. Mumford and J. Shah (1988). they show that for real images the problem of the choice of the energy functional is dictated by the model of the world, and they propose a method to optimize it based on a deterministic algorithm processed at multiple levels of resolution. Problems encountered in dealing with real scenes lead to several modifications of the algorithm and the energy functional. images are shown on which the algorithm was tested.< >

关键词： image segmentation Layout image processing image analysis image reconstruction Approximation methods Light sources Energy measurement

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Extracting projective structure from single perspective views of 3D point sets

Extracting projective structure from single perspective view...

引用

international conference on computer vision (ICCV)

作者： C.A. Rothwell D.A. Forsyth A. Zisserman J.L. Mundy Department of Engineering Science University of Oxford Oxford UK

A number of recent papers have argued that invariants do not exist for three-dimensional point sets in general position, which has often been misinterpreted to mean that invariants cannot be computed for any three-dimensional structure. It is proved by example that although the general statement is true, invariants do exist for structured three-dimensional point sets. Projective invariants are derived for two object classes: the first is for points that lie on the vertices of polyhedra, and the second for objects that are projectively equivalent to ones possessing a bilateral symmetry. the motivations for computing such invariants are twofold: they can be used for recognition, and they can be used to compute projective structure. Examples of invariants computed from real images are given.< >

关键词： Geometry Testing computer vision image recognition Calibration Indexing Libraries Position measurement

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2-D digital curve analysis: A regularity measure

2-D digital curve analysis: A regularity measure

引用

international conference on computer vision (ICCV)

作者： B. Vasselle G. Giraudon INRIA Sophia-Antipolis France

A regularity measure for discrete line geometry is presented. this quantitative measure based on a ratio between line lengths at different scales is analyzed in the framework of Brownian motion theory. the measure at a given scale is always computed from the maximum precision image, so that it does not introduce any subresolution assumption. A scale choice determines the quantity of global information vs. local information to be measured. Its statistical behavior is studied on two extremal models of curves: the Brownian motion and the digitized straight line. It is shown that this quantitative measure leads to relevant shape information. To illustrate this fact, an image segmentation application example is discussed based essentially on geometry criteria of region boundaries. Some experimental results performed on real-scene images are presented.< >

关键词： Shape Fractals Geometry Length measurement Motion measurement Brownian motion image segmentation Humans image motion analysis image recognition

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Reactions to peripheral image motion using a head/eye platform

Reactions to peripheral image motion using a head/eye platfo...

引用

international conference on computer vision (ICCV)

作者： D.W. Murray P.F. McLauchlan I.D. Reid P.M. Sharkey Department of Engineering Science University of Oxford Oxford UK

the authors demonstrate four real-time reactive responses to movement in everyday scenes using an active head/eye platform. they first describe the design and realization of a high-bandwidth four-degree-of-freedom head/eye platform and visual feedback loop for the exploration of motion processing within active vision. the vision system divides processing into two scales and two broad functions. At a coarse, quasi-peripheral scale, detection and segmentation of new motion occurs across the whole image, and at fine scale, tracking of already detected motion takes place within a foveal region. Several simple coarse scale motion sensors which run concurrently at 25 Hz with latencies around 100 ms are detailed. the use of these sensors are discussed to drive the following real-time responses: (1) head/eye saccades to moving regions of interest; (2) a panic response to looming motion; (3) an opto-kinetic response to continuous motion across the image and (4) smooth pursuit of a moving target using motion alone.< >

关键词： Head Motion detection Layout Feedback loop Machine vision image segmentation Tracking Delay image sensors Drives

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Direct estimation of multiple disparities for transparent multiple surfaces in binocular stereo

Direct estimation of multiple disparities for transparent mu...

引用

international conference on computer vision (ICCV)

作者： M. Shizawa ATR Human Information Processing Research Laboratories Japan

A closed-form single-shot stereo disparity estimation algorithm is proposed that can compute multiple disparities due to transparency directly from signal differences and variations on epipolar lines of a binocular image pair. the transparent stereo constraint equations have been derived by using a novel mathematical technique, the principle of superposition. A computationally tractable single-shot algorithm is derived by using the first-order approximation of the constraint equations with respect to disparities. the algorithm can compute multiple disparities from only two images, in contrast to the previous algorithms for motion transparency, which needed at least n+1 frames for n simultaneous motion estimates. the derived algorithm can be viewed as the SSD (sum of squared differences) for signal matching extended to deal with multiple disparities. However, the constraints are not dedicated solely to the SSD method and several other implementations are possible.< >

关键词： Stereo vision computer vision Humans Layout Quantum computing image motion analysis Laboratories Information processing Telecommunication computing Signal processing

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Learning object recognition models from images

Learning object recognition models from images

引用

international conference on computer vision (ICCV)

作者： A.R. Pope D.G. Lowe Department of Computer Science University of British Columbia Vancouver BC Canada

To recognize an object in an image an internal model is required to indicate how that object may appear. the authors show how to learn such a model from a series of training images depicting a class of objects, producing a model that represents a probability distribution over the variation in object appearance. Features identified in an image through perceptual organization are represented by a graph whose nodes include feature labels and numeric measurements. A learning procedure generalizes multiple image graphs to form a model graph in which the numeric measurements are characterized by probability distributions. A matching procedure, using a similarity metric based on a non-parametric probability density estimator, compares model and image graphs to identify an instance of a modeled object in an image. Experimental results are presented from a system constructed to test this approach. the system learns to recognize partially occluded 2-D objects in 2-D images using shape cues. It can recognize objects as similar in general appearance while distinguishing them by their detailed features.< >

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