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Method for recovering three-dimensional geometric information from image

A technology in 3D geometry and images, applied in the field of computer vision, can solve problems such as difficult heuristic constraints

Inactive Publication Date: 2009-04-01
PEKING UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Many monocular cues not only rely on prior knowledge, but also rely on the overall context information, so it is not only difficult to use heuristic constraints, but also difficult to speculate from the local part of the image

Method used

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  • Method for recovering three-dimensional geometric information from image
  • Method for recovering three-dimensional geometric information from image
  • Method for recovering three-dimensional geometric information from image

Examples

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Embodiment Construction

[0037] The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0038] The technical solution of the present invention is briefly described as follows: firstly, training data is acquired. Use a laser scanner and a calibrated camera to simultaneously acquire a picture of the scene and its corresponding depth map; then extract features from each image in the training library, and use a joint Laplacian Markov random field model to describe the image features Corresponding to the probability of different depths and the relationship between the depth values ​​of adjacent positions, the model parameters are obtained by learning the training library. Then build a two-layer graph structure to combine high-resolution binocular cues and low-resolution monocular cues; use the parameters obtained in the previous step to define the energy term of the image block layer, and add it as a constraint to the traditio...

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Abstract

The invention relates to a method for restoring 3D geometric information from images. The method comprises the following steps: a large amount of scene images and the corresponding depth maps thereof are obtained and used as a training library; the images are divided into image blocks, the probabilities thereof corresponding to different depths are described by the statistical learning method to obtain different parameter values; a graph structure including an image block layer, a pixel layer, and the edges connecting the pixels and the corresponding image blocks is constructed for the image pairs used for the scene reconstruction; the energy term of the graph structure is defined by the parameters obtained from the statistical learning; the energy term is taken as a constraint and added to an image describing parallax relation among pixels based on the conventional stereo matching; and a parallax image of the two images is solved.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method for recovering three-dimensional geometric information from images. Background technique [0002] Stereo matching has been an important problem in computer vision and photogrammetry. The two images record real-world scenes at very close angles of view. Binocular cues refer to the different positions of objects projected on the two imaging planes. The difference in position changes with the depth of the object. In the past few decades, a large number of stereo vision systems have been proposed, making great progress in the research in this field. However, due to the morbidity of the problem itself, it still has not been completely resolved. [0003] Among existing stereo matching methods, graph-based methods are the most popular techniques. It can obtain a smooth disparity map that matches the observed data. A typical approach is to use graph cuts to optimize the energy...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 马祥音李仁举查红彬英向华
Owner PEKING UNIV
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