In binocular visual systems, vergence is the process of directing the gaze so that the optical axes intersect at a surface point. Correlation-based methods of disparity analysis provide fast estimates of the vergence ...
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In binocular visual systems, vergence is the process of directing the gaze so that the optical axes intersect at a surface point. Correlation-based methods of disparity analysis provide fast estimates of the vergence error. Unfortunately most correlation techniques do not provide mechanisms to determine which image locations contributed to a given correlation peak. The result is that large correlation peaks may have contributions from image arena not relevant to the vergence task. This paper presents a vergence system that applies a cepstral filter to multiscale images obtained from a dominant-eye binocular sensor. As used by this system, the cepstral filter has two main advantages: it enhances targets through narrow-band signal suppression, and it supports a back-projection operation to determine the image locations associated with particular correlation peaks. The use of multiscale images allows the system to have both high resolution for precision in the final vergence and a large field of view for a wide range of initial camera orientations without undue computational cost.< >
There are two basic problems concerned with Gabor filterings that we will address in this paper. One is the window size problem, in which we will adopt a set of 2D variable window Gabor filters, and compare its perfor...
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There are two basic problems concerned with Gabor filterings that we will address in this paper. One is the window size problem, in which we will adopt a set of 2D variable window Gabor filters, and compare its performance with those of fixed window filters. We will show that the variable window scheme is more adaptive to image contents. The other problem we will address is the stability of amplitude and phase information resulting from convolving the filters with images. We will extend Fleet's 1D phase stability analysis to 2D phase and amplitude stability analysis based upon the assumption of local resemblance of filter outputs to a single sinusoid. Applications on focus quality measurement and 2D correspondence are described, and the results demonstrate improvements of performance by detecting unstable information using the criterion developed.< >
Texture features have been among major tools in image analysis field for decades. Their applications in various computerized biomedical imageprocessing.teak advantage of the fact that computers are better than human ...
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Texture features have been among major tools in image analysis field for decades. Their applications in various computerized biomedical imageprocessing.teak advantage of the fact that computers are better than human observers at analyzing second order statistics. The attempt to make use of a similar approach to provide additional insight into EEG patternrecognition was presented by A. Petrosian et al. (Annual Meeting of the American EEG society, New Orleans, LA, USA, p.88, Oct. 10-15, 1993). This study represents further development of suggested methods in recognition of different interictal, preictal, ictal, and postictal stages from EEG recordings. Practical application that is relevant to this study includes prediction of epileptic activity in patients before an actual seizure occurs. Although this study is preliminary and was carried out on the data obtained from one patient, the results showed feasibility of using signal texture information for distinguishing different abnormal patterns.< >
This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and un...
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This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.< >
We previously presented (Sarkar and Boyer, 1993) the Perceptual Inference Network (PIN), a formalism based on Bayesian Networks, to reason among a set of object or feature hypotheses and to integrate multiple sources ...
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We previously presented (Sarkar and Boyer, 1993) the Perceptual Inference Network (PIN), a formalism based on Bayesian Networks, to reason among a set of object or feature hypotheses and to integrate multiple sources of information in the context of perceptual organization. The design of a PIN requires knowledge of the dependency structure among the organizations of interest and the specification of the conditional probabilities. This design was done manually with large doses of tedium and guesswork. In this paper we present an algorithm based on structural entropic measures and random parametric structural descriptions (RPSDs) to design a PIN automatically and in a (more) theoretically sound fashion. Experimental results present evidence of the robustness of the algorithm and make performance comparisons on real image data with a manually structured PIN. Since PINs are a form of Bayesian Network, we hope that this work will also prove useful towards structuring Bayesian Networks in other computer vision contexts.< >
This paper develops a new class of physics-based deformable models which can deform both globally and locally. Their global parameters are functions allowing the definition of new parameterized primitives and paramete...
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This paper develops a new class of physics-based deformable models which can deform both globally and locally. Their global parameters are functions allowing the definition of new parameterized primitives and parameterized global deformations. These new global parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional bending and twisting. Using a physics-based approach we convert these geometric models into deformable models that deform due to forces exerted from the data-points so as to conform to the given dataset. We present an experiment involving the extraction of shape and motion of the Left Ventricle (LV) of a heart from MRI-SPAMM data based on a few global parameter functions.< >
We present a method to locate an `object' in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color, which permits the use of color-space pr...
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ISBN:
(纸本)081863880X
We present a method to locate an `object' in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color, which permits the use of color-space processing. A new method is presented, which exploits more information than the previous Backprojection Algorithm of Swain and Ballard at a competitive complexity. Precisely, the new algorithm is based on matching local histograms with the model, instead of directly replacing pixels with a confidence that they belong to the object. We prove that a simple version of this algorithm degenerates into Backprojection in the worst case. In addition, we show how to estimate the scale of the model. We also propose the use of co-occurrence histograms to deal with cases where important color variations can be expected. Results are shown on pictures digitized from the famous `Waldo' books.
We introduce a hierarchical color segmentation technique that combine the advantages of local (simplicity and quickness) and global region growing methods (robustness, accuracy, avoidance of chaining mismatches). The ...
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ISBN:
(纸本)081863880X
We introduce a hierarchical color segmentation technique that combine the advantages of local (simplicity and quickness) and global region growing methods (robustness, accuracy, avoidance of chaining mismatches). The method is implemented for a traffic sign recognition system.
Space curves are efficient, highly descriptive features of 3-D objects. This paper introduces a new multi-scale shape representation (the Resampled Torsion Scale Space (or TSS) image) for space curves suitable for rec...
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ISBN:
(纸本)081863880X
Space curves are efficient, highly descriptive features of 3-D objects. This paper introduces a new multi-scale shape representation (the Resampled Torsion Scale Space (or TSS) image) for space curves suitable for recognition of a noisy curve at any scale or orientation. A two-phase matching algorithm consisting of TSS matching (using extrema of TSS zero-crossing contours) followed by transformation parameter optimization demonstrates the usefulness of the representations in recognition tasks.
In this paper we show that a 3D volumic image can be considered as a hypersurface in R4. As an illustration, we derive an algorithm for extracting the ridge lines of the surfaces traced by the iso-contours.
ISBN:
(纸本)081863880X
In this paper we show that a 3D volumic image can be considered as a hypersurface in R4. As an illustration, we derive an algorithm for extracting the ridge lines of the surfaces traced by the iso-contours.
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