Optimal neighborhood picture group selection method for depth map calculation

A technology of neighborhood images and depth maps, which is applied in the field of optimal neighborhood image group selection, can solve problems such as unguaranteed results, and achieve the effect of high-precision depth maps

Inactive Publication Date: 2014-04-02
INST OF AUTOMATION CHINESE ACAD OF SCI
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This method is robust to image scale changes, but still can

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  • Optimal neighborhood picture group selection method for depth map calculation
  • Optimal neighborhood picture group selection method for depth map calculation
  • Optimal neighborhood picture group selection method for depth map calculation

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[0020] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0021] The present invention proposes a method for selecting the optimal neighborhood image group for depth map calculation, which enables it to efficiently select the optimal neighborhood image group from a large number of images, so as to obtain a high-precision depth map on the reference image the goal of.

[0022] figure 1 It is a flow chart of the method for selecting the optimal neighborhood image group for depth map calculation in the present invention.

[0023] For a given reference image, in order to calculate the depth map on this reference image, it is necessary to select a given number of neighboring images in the adjacent images of this image to form a stereoscopic image group for depth calculation. The pre...

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Abstract

The invention discloses an optimal neighborhood picture group selection method for depth map calculation. The method is characterized by comprising the following steps: 1. extracting affine invariant feature points on a reference picture and other pictures, matching the detected feature points, and calculating the spatial positions of the feature points; 2. randomly selecting a given number of pictures from all pictures, except for the reference picture, to form a candidate neighborhood picture group, and calculating the consistency degree of the reference picture and the candidate neighborhood picture group; 3. carrying out iteration on the candidate neighborhood picture group by using a quantum evolutionary algorithm so as to continuously improve the consistency degree, wherein the picture group obtained when the iteration is over serves as an optimal neighborhood picture group. By utilizing the method provided by the invention, the optimal neighborhood picture group can be efficiently selected from a great amount of pictures, so that the purpose of obtaining a high-precision depth map on the reference picture can be achieved.

Description

technical field [0001] The invention relates to a method for selecting neighborhood images in the field of computer vision, in particular to a method for selecting an optimal neighborhood image group for depth map calculation. Background technique [0002] For a reference image, obtaining a depth map from multiple adjacent images is one of the important research directions of computer vision, which has a wide range of applications in 3D reconstruction, visual navigation, scene understanding, etc. In the process of calculating the depth map of the reference image, how to select the optimal neighborhood image group from a large number of images has an important impact on the integrity and accuracy of the depth map calculation, and the existing methods are still unable to effectively select the optimal neighborhood image group. [0003] Through literature search of the prior art, it is found that M. Goesele is equal to the paper "Multiview stereo for community photo collection...

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Application Information

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IPC IPC(8): G06T7/00G06K9/64G06K9/46
Inventor 申抒含胡占义
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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