A local parallel method is described for computing the stochastic completion field introduced in an earlier report. The local parallel method can be interpreted as a stable finite difference scheme for solving the und...
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ISBN:
(纸本)0818672587
A local parallel method is described for computing the stochastic completion field introduced in an earlier report. The local parallel method can be interpreted as a stable finite difference scheme for solving the underlying Fokker-Planck equation identified by Mumford. The new method is more plausible as a neural model since (1) unlike the previous method, it can be computed in a sparse, locally connected network;and (2) the network dynamics are consistent with psycophysical measurements of the time course of illusory contour formation.
We propose a new method for view synthesis from real images using stereo vision. The method does not explicitly model scene geometry, and enables fast and exact generation of synthetic views. We also reevaluate the re...
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ISBN:
(纸本)0818672587
We propose a new method for view synthesis from real images using stereo vision. The method does not explicitly model scene geometry, and enables fast and exact generation of synthetic views. We also reevaluate the requirements on stereo algorithms for the application of view synthesis and discuss ways of dealing with partially occluded regions of unknown depth and with completely occluded regions of unknown texture. Our experiments demonstrate that it is possible to efficiently synthesize realistic new views even from inaccurate and incomplete depth information.
Previous work [5], [2] have developed an approach for estimating shape and albedo from multiple images assuming Lambertian reflectance with single light sources. The main contributions of this paper are: (i) to show h...
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ISBN:
(纸本)0780342364
Previous work [5], [2] have developed an approach for estimating shape and albedo from multiple images assuming Lambertian reflectance with single light sources. The main contributions of this paper are: (i) to show how the approach can be generalized to include ambient background illumination, (ii) to demonstrate the use of the integrability constraint for solving this problem, and (iii) an iterative algorithm which is able to improve the analysis by finding shadows and rejecting them.
Current methods for registering image regions perform well for simple transformations or large image regions. In this paper, we present a new method that is better able to handle small image regions as they deform wit...
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ISBN:
(纸本)0780342364
Current methods for registering image regions perform well for simple transformations or large image regions. In this paper, we present a new method that is better able to handle small image regions as they deform with non-linear transformations. We introduce difference decompositon, a novel approach to solving the registration problem. The method is a generalization of previous methods and can better handle non-linear transforms. Although the methods are general, we focus on projective transformations and introduce piecewise-projective transformations for modeling the motions of non-planar objects. We conclude with examples from our prototype implementation.
We develop a simple and very fast method for object tracking based exclusively on color information in digitized video images. Running on a Silicon Graphics R4600 Indy system with an IndyCam, our algorithm is capable ...
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ISBN:
(纸本)0780342364
We develop a simple and very fast method for object tracking based exclusively on color information in digitized video images. Running on a Silicon Graphics R4600 Indy system with an IndyCam, our algorithm is capable of simultaneously tracking objects at full frame size (640 x 480 pixels) and video frame rate (30 fps). Robustness with respect to occlusion is achieved via an explicit hypothesis-tree model of the occlusion process. We demonstrate the efficacy of our technique in the challenging task of tracking people, especially tracking human heads and hands.
In the depth from defocus (DFD) method two defocused images of a scene are obtained by capturing the scene with different sets of camera parameters. An arbitrary selection of the camera settings can result in observed...
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ISBN:
(纸本)0780342364
In the depth from defocus (DFD) method two defocused images of a scene are obtained by capturing the scene with different sets of camera parameters. An arbitrary selection of the camera settings can result in observed images whose relative blurring is insufficient to yield a good estimate of the depth. In this paper, we study the effect of the degree of relative blurring on the accuracy of the estimate of the depth by addressing the DFD problem in a maximum likelihood-based framework. We propose a criterion for optimal selection of camera parameters to obtain an improved estimate of the depth. The optimality criterion is based on the Cramer-Rao bound of the variance of the error in the estimate of blur. Simulations as well as experimental results on real images are presented for validation.
In this paper, we present a new approach to extract characters on a license plate of a moving vehicle given a sequence of perspective distortion corrected license plate images. We model the extraction of characters as...
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ISBN:
(纸本)0780342364
In this paper, we present a new approach to extract characters on a license plate of a moving vehicle given a sequence of perspective distortion corrected license plate images. We model the extraction of characters as a Markov random field (MRF), With the MRF modeling, the extraction of characters is formulated as the problem of maximizing the a posteriori probability based on given prior and observations. A genetic algorithm with local greedy mutation operator is employed do optimize the objective function. Experiments and comparison study were conducted. It is shown that our approach provides better performance than other single frame methods.
This paper addresses the problem of estimating the epipolar geometry from point correspondences between two images taken by uncalibrated perspective cameras. It is shown that Jepson's and Heeger's linear subsp...
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ISBN:
(纸本)0818672587
This paper addresses the problem of estimating the epipolar geometry from point correspondences between two images taken by uncalibrated perspective cameras. It is shown that Jepson's and Heeger's linear subspace technique for infinitesimal motion estimation can be generalized to the finite motion case by choosing an appropriate basis for projective space. This yields a linear method for weak calibration. The proposed algorithm has been implemented and tested on both real and synthetic images, and it is compared to other linear and non-linear approaches to weak calibration.
We present a new approach for resolving occlusions in augmented reality. The main interest is that it does not require 3D reconstruction of the considered scene. Our idea is to use a contour based approach and to labe...
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ISBN:
(纸本)0780342364
We present a new approach for resolving occlusions in augmented reality. The main interest is that it does not require 3D reconstruction of the considered scene. Our idea is to use a contour based approach and to label each contour point as being ''behind'' or ''in front of'', depending on whether it is in front of or behind the virtual object. This labeling step only requires that the contours can be tracked from frame to frame. A proximity graph is then built in order to group the contours that belong to the same occluding object. Finally, we use some kind of active contours to accurately recover the mask of the occluding object.
This paper introduces a unified approach to the problem of verifying Alignment hypotheses in the presence of substantial amounts of uncertainty in the predicted locations of projected model features. Our approach is i...
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ISBN:
(纸本)0780342364
This paper introduces a unified approach to the problem of verifying Alignment hypotheses in the presence of substantial amounts of uncertainty in the predicted locations of projected model features. Our approach is independent of whether the uncertainty is distributed or bounded, and, moreover, incorporates information about the domain in a formally correct manner. Information which can be incorporated includes the error model, the distribution of background features, and the positions of the data features near each predicted model feature. Experiments are described that demonstrate the improvement over previously used methods. Furthermore, our method is efficient in that the number of operations is on the order of the number of image features that lie nearby the predicted model features.
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