Computer vision publications
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Self-Consistency, A Novel Approach to Characterizing the Accuracy and Reliability of Point-Correspondence Algorithms
We present a framework for reliably and robustly detecting changes in terrain (or other 3-D objects) over time.
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A Framework for Detecting Changes in Terrain
We propose a methodology that estimates the accuracy and reliability of the results of any multiple-image point correspondence algorithm, without the need for ground truth or camera calibration.
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Using Differential Constraints to Reconstruct Complex Surfaces from Stereo
Stereo reconstruction algorithms often fail to properly deal with complex surfaces, because there is not enough image information. We propose to guide the reconstruction process using a priori information about the differential geometry of the object surfaces.
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Object-Centered Surface Reconstruction: Combining Multi-Image Stereo and Shading
We argue that an object-centered representation is most appropriate for this purpose becasue it naturally accomodates multiple sources of data, multiple images (including motion sequences of a rigid object), and self-occlusions.
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Registration without Correspondences
We present a method for registering images of complex 3-D surfaces that does not require explicit correspondences between features across the images.
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Using 3-Dimensional Meshes to Combine Image-Based and Geometry Constraints
A unified framework for 3-D shape reconstruction allows us to combine image-based and geometry-based information sources. The image information is akin to stereo and shape-from-shading, while the geometric information may be provided in the form of 3-D points, 3-D features or 2-D silhouettes.
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Learning Control Parameters of a Vision Process Using Contextual Information
This paper presents a method for the system itself to learn how to select among its algorithms and to set their parameters, reducing the need for operator expertise while improving efficiency at the same time.
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Building and Using Scene Repesentations In Image Understanding
The analysis side is the processing of sensory data for such tasks as recognition and navigation, and a number of techniques are discussed here for dealing with these two-, three-, and higher-dimensional data.
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Overview Of The SRI Cartographic Modeling Environment
The SRI Cartographic Modeling Environment has been created to support research on interactive, semi-automated, and automated computer-based cartographic activities. The underlying image manipulation capabilities are provided by the SRI ImagCalc system.
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Fast Parallel Surface Interpolation With Applications To Digital Cartography
In this paper, we present a surface interpolation algorithm based on variational splines which is well suited to massively parallel computers.
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Recognizing Objects In A Natural Environment: A Contextual Vision (CVS)
We identify a number of weaknesses in current recognition systems and propose specific mechanisms for dealing with some of these problems.
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The Vision Problem: Exploiting Parallel Computation
This technical report consists of papers presented at the session wherein the major problems in computer vision are outlined, and the “signals to symbols”and the “monolithic computing” (MC) approaches to these problems are described.