3D Object Modeling and Recognition from Photographs and Image Sequences

Rothganger, Fred; Lazebnik, Svetlana; Schmid, Cordelia; Ponce, Jean

doi:10.1007/11957959_6

Cited by 8 publications

(3 citation statements)

References 47 publications

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“…Then, a standard stereo matching algorithm that searches for matching patches along corresponding epipolar lines is used to determine an initial set of tentative matches. We use a combination of SIFT [5] and the color histogram descriptor described in [10] to compute the initial matches. The matches are then refined to obtain the correct alignment of the patches in the left and right images.…”

Section: Stereo Modelingmentioning

confidence: 99%

“…First, we solve for the patch centers in 3D by using standard calibrated stereo triangulation. Then, we reconstruct the edges of the corresponding parallelograms using a first-order approximation to the perspective projection equations in the vicinity of the patch centers as proposed by Rothganger [10]. This gives us a partial 3D model of the object for each stereo pair.…”

Section: Model Constructionmentioning

confidence: 99%

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Modeling 3D Objects from Stereo Views and Recognizing Them in Photographs

Kushal

Ponce

2006

Computer Vision – ECCV 2006

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Local appearance models in the neighborhood of salient image features, together with local and/or global geometric constraints, serve as the basis for several recent and effective approaches to 3D object recognition from photographs. However, these techniques typically either fail to explicitly account for the strong geometric constraints associated with multiple images of the same 3D object, or require a large set of training images with much overlap to construct relatively sparse object models. This paper proposes a simple new method for automatically constructing 3D object models consisting of dense assemblies of small surface patches and affine-invariant descriptions of the corresponding texture patterns from a few (7 to 12) stereo pairs. Similar constraints are used to effectively identify instances of these models in highly cluttered photographs taken from arbitrary and unknown viewpoints. Experiments with a dataset consisting of 80 test images of 9 objects, including comparisons with a number of baseline algorithms, demonstrate the promise of the proposed approach.

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Section: Stereo Modelingmentioning

confidence: 99%

Section: Model Constructionmentioning

confidence: 99%

Modeling 3D Objects from Stereo Views and Recognizing Them in Photographs

Kushal

Ponce

2006

Computer Vision – ECCV 2006

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“…Much progress has been made in the recent past both in recognizing individual objects [2,7], while some groups have interpreted this task as a wide-baseline problem, and register pairs of images to build a 3D model used for recognition [9].…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Cascade of Detectors for Individual Object Recognition

Moreels

Perona

2008

Lecture Notes in Computer Science

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Abstract.A probabilistic system for recognition of individual objects is presented. The objects to recognize are composed of constellations of features, and features from a same object share the common reference frame of the image in which they are detected. Features appearance and pose are modeled by probabilistic distributions, the parameters of which are shared across features in order to allow training from few examples.In order to avoid an expensive combinatorial search, our recognition system is organized as a cascade of well-established, simple and inexpensive detectors. The candidate hypotheses output by our algorithm are evaluated by a generative probabilistic model that takes into account each stage of the matching process.We apply our ideas to the problem of individual object recognition and test our method on several data-sets. We compare with Lowe's algorithm [7] and demonstrate significantly better performance.

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Building Survey System for the Representation of the Load-Bearing Structure

Bourlotos¹,

Dan

2016

Space and Time Visualisation

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3D Object Modeling and Recognition from Photographs and Image Sequences

Cited by 8 publications

References 47 publications

Modeling 3D Objects from Stereo Views and Recognizing Them in Photographs

Modeling 3D Objects from Stereo Views and Recognizing Them in Photographs

A Probabilistic Cascade of Detectors for Individual Object Recognition

Building Survey System for the Representation of the Load-Bearing Structure

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