Local image describing method based on RGB-D sensor

A RGB image, RGB-D technology, applied in the field of RGB-D image matching

Active Publication Date: 2015-07-15
ZHEJIANG UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a local image description met

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Embodiment Construction

[0038] The method of the present invention is based on the local image description of the RGB-D sensor, and the inventive method comprises the following steps:

[0039] 1. Calibrate the parameters of the RGB-D sensor according to the OPENNI open source library or the Microsoft development toolkit, and obtain the RGB image and the depth image; the RGB image and the depth image under the focal plane coordinate system (O′) are obtained according to the conversion formula in the world coordinate system (O u ) under the point cloud data;

[0040] Step 2: Perform image preprocessing and local feature extraction on the RGB image and depth image obtained in step 1; image preprocessing is to use Gaussian filtering on the RGB image and depth image, and local feature extraction is to use Hasson affine / Harry on the RGB image Hessian-affine / Harris-affine (Hessian-affine / Harris-affine) extracts local features, obtains several local features, and takes the center point of the local features ...

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Abstract

The invention provides a local image describing method based on an RGB-D sensor. The local image describing method comprises the following steps: calibrating parameters of the RGB-D sensor, and carrying out image pretreatment and local characteristic extraction on acquired RGB images and depth images; expressing the central point of the extracted local characteristics through three variables of space partitioning, grayness sequence marking and normal vector sequence marking; calculating out the scale value and the principal direction of characteristic points according to the data of the depth images in the central point of the local characteristics; building a three-dimensional histogram, unfolding the three-dimensional histogram and normalizing the three-dimensional histogram to be a one-dimensional vector which is a descriptor for the local characteristics. Compared with two-dimensional, three-dimensional and fusion descriptors, the method has the advantages of obvious lighting robustness and the scene changeable robustness. Based on depth scale invariance and rotating invariance, in the method provided by the invention, point cloud depth data is used for replacing estimation to the scale space of a Gauss pyramid, so that the speed is accelerated greatly.

Description

technical field [0001] The invention relates to a method for matching data such as an image of an RGB-D sensor and a point cloud, in particular to a method for realizing RGB-D image matching by fusing RGB image texture information and a depth image. Background technique [0002] The local image description method based on RGB-D sensor is inspired by the local feature neighborhood description of 2D images and depth images. Two-dimensional images have rich textures and high information entropy. Therefore, the two-dimensional descriptors that exist at this stage start with spatial partitioning, grayscale, gradient, etc., and have good results, but the two-dimensional descriptors are not ideal for scenes with less lighting or texture changes. In a scene based entirely on a depth image, the depth image will not be affected by missing textures or dramatic lighting changes. Building various descriptors on this basis has a good matching effect, but the matching results of such desc...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 刘勇冯光华
Owner ZHEJIANG UNIV
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