Three-dimensional model local spherical harmonic feature extraction method
A 3D model and feature extraction technology, applied in the field of computer vision, can solve problems such as loss of structural information
Active Publication Date: 2014-04-02
广东相控信息科技有限公司
View PDF1 Cites 9 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
It can be seen that although it is called the 3D LBP algorithm, the calculation is not really performed in the 3D data, but is applied to the depth image of the 3D image. Although the depth image can represent the structural information of the 3D image, the depth image is The projection result of a certain direction of the 3D image will inevitably cause the loss of some structural information, so it should actually be called 2.5D LBP algorithm
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0058] The method of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0059] All the experimental data in the examples come from the 3D human ear database in the Collection J2 sub-library in the UND 3D human ear database, which includes 415 people, 5-6 groups of 3D model data and corresponding 2D images for each person. The objective of the embodiment is to verify the validity of the local spherical harmonic feature extraction of the three-dimensional model proposed by the present invention through the three-dimensional model recognition result. In the implementation process, each person randomly selects 2 groups of 3D model data and corresponding 2D images, of which 1 group is used as a training sample and the other group is used as a test sample, and the human ear region detection and segmentation are completed for each group of data. Then, use the local spherical harmonic feature extrac...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses a three-dimensional model local spherical harmonic feature extraction method and belongs to the field of computer vision. The three-dimensional model local spherical harmonic feature extraction method is characterized in that the local spherical harmonic feature extraction method is provided in allusion to the defect that in the existing three-dimensional model global spherical harmonic feature extraction method, the selection deviation of the centre of sphere has a strong impact on the subsequent spherical surface sampling and feature extraction. The method comprises the steps of performing dimension normalization processing on a three-dimensional model; performing resampling on three-dimensional data by using an interpolation method so as to generate a depth image, and performing mesh generation on the depth image so as to determine positions of local centers of sphere; performing local spherical surface sampling on each local center of sphere by using a homocentric spherical shell method; calculating a spherical harmonic feature vector corresponding to each local center of sphere, and using a weighted array method to obtain local spherical harmonic feature vectors of the whole three-dimensional model. By using the method, the instability caused by the position deviation of the centre of sphere can be relieved to some extent, and an excellent basis is provided for subsequent recognition.
Description
technical field [0001] The invention belongs to the field of computer vision, and relates to spherical harmonic transformation, three-dimensional model feature extraction and other technologies. Background technique [0002] Summarizing the existing 3D model recognition methods, there are two main methods of feature extraction: one is the feature extraction method based on the depth map, and the other is the method based on the 3D data itself. The feature extraction method based on the depth map first corrects the pose of the 3D model, then generates the depth map, and finally uses the 2D feature extraction method to perform feature extraction on the depth map. Although the depth map can represent the shape characteristics of 3D data at a certain level, it is a depth projection in a certain aspect after all, so the selection of the projection direction is a very important process. In general, it is necessary to analyze the 3D model before projection. Perform attitude rotati...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06T15/00
Inventor 曾慧张瑞穆志纯黄明明张保庆
Owner 广东相控信息科技有限公司