42 Result(s)
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Chapter and Conference Paper
Finding pictures of objects in large collections of images
Retrieving images from very large collections, using image content as a key, is becoming an important problem. Users prefer to ask for pictures using notions of content that are strongly oriented to the presen...
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Chapter and Conference Paper
Finding boundaries in natural images: A new method using point descriptors and area completion
We develop an approach to image segmentation for natural scenes containing image texture. One general methodology which shows promise for solving this problem is to characterize textured regions via their resp...
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Chapter and Conference Paper
Region-Based Image Retrieval
As the world becomes an increasingly networked place, effective access to information grows ever more important. This access can take several forms, including traditional database retrieval of structured infor...
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Chapter
Grou** in the Normalized Cut Framework
In this paper, we study low-level image segmentation in the normalized cut framework proposed by Shi and Malik (1997). The goal is to partition the image from a big picture point of view. Perceptually signific...
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Chapter and Conference Paper
Blobworld: A System for Region-Based Image Indexing and Retrieval
Blobworld is a system for image retrieval based on finding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions (“blobs”) with associated color and tex...
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Chapter
Contour and Texture Analysis for Image Segmentation
This paper provides an algorithm for partitioning gray-scale images into disjoint regions of coherent brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour...
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Article
Contour and Texture Analysis for Image Segmentation
This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour ...
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Chapter and Conference Paper
Spectral Partitioning with Indefinite Kernels Using the Nyström Extension
Fowlkes et al. [7] recently introduced an approximation to the Normalized Cut (NCut) grou** algorithm [18] based on random subsampling and the Nyström extension. As presented, their method is restricted to the ...
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Chapter and Conference Paper
Approximate Thin Plate Spline Map**s
The thin plate spline (TPS) is an effective tool for modeling coordinate transformations that has been applied successfully in several computer vision applications. Unfortunately the solution requires the inve...
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Chapter and Conference Paper
On Refractive Optical Flow
This paper presents a novel generalization of the optical flow equation to the case of refraction, and it describes a method for recovering the refractive structure of an object from a video sequence acquired ...
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Chapter and Conference Paper
A Feature-Based Approach for Determining Dense Long Range Correspondences
Planar motion models can provide gross motion estimation and good segmentation for image pairs with large inter-frame disparity. However, as the disparity becomes larger, the resulting dense correspondences wi...
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Chapter and Conference Paper
Structure from Periodic Motion
We show how to exploit temporal periodicity of moving objects to perform 3D reconstruction. The collection of period-separated frames serve as a surrogate for multiple rigid views of a particular pose of the m...
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Chapter and Conference Paper
Practical Global Optimization for Multiview Geometry
This paper presents a practical method for finding the provably globally optimal solution to numerous problems in projective geometry including multiview triangulation, camera resectioning and homography estim...
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Article
A Feature-based Approach for Dense Segmentation and Estimation of Large Disparity Motion
We present a novel framework for motion segmentation that combines the concepts of layer-based methods and feature-based motion estimation. We estimate the initial correspondences by comparing vectors of filte...
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Chapter and Conference Paper
Multiple Component Learning for Object Detection
Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, achieving very low false positives rates...
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Chapter and Conference Paper
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learning object classifiers from we...
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Article
Practical Global Optimization for Multiview Geometry
This paper presents a practical method for finding the provably globally optimal solution to numerous problems in projective geometry including multiview triangulation, camera resectioning and homography esti...
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Chapter and Conference Paper
Word Spotting in the Wild
We present a method for spotting words in the wild, i.e., in real images taken in unconstrained environments. Text found in the wild has a surprising range of difficulty. At one end of the spectrum, Optical Chara...
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Chapter and Conference Paper
Visual Recognition with Humans in the Loop
We present an interactive, hybrid human-computer method for object classification. The method applies to classes of objects that are recognizable by people with appropriate expertise (e.g., animal species or airp...
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Article
Open AccessGlobally Optimal Algorithms for Stratified Autocalibration
We present practical algorithms for stratified autocalibration with theoretical guarantees of global optimality. Given a projective reconstruction, we first upgrade it to affine by estimating the position of t...
