Three-dimensional auricle point cloud shape feature matching method based on IsoRank algorithm
A technology of shape features and matching methods, applied in computing, image data processing, 3D modeling, etc., to achieve the effect of improving registration accuracy and matching efficiency and reducing the amount of data
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[0016] a. Based on the PCA method, analyze the shape features in the local neighborhood sphere of the auricle point cloud, and extract the shape key points of the auricle point cloud;
[0017] For any auricle point cloud M, randomly select a data point p on M, if the distance d between point p and the edge of the auricle is greater than a given threshold δ (here let δ=r+10mm), point p is called a seed point , denoted as fp; take any seed point fp as the center, make a ball with r as the radius, and perform principal component analysis (PCA, Principal Component Analysis) on all the data points in the ball to obtain the eigenvector matrix M evec and the eigenvalue matrix M eval ;Project all points in the sphere onto the eigenvectors corresponding to the two larger eigenvalues, remember the difference between the maximum value and minimum value projected in the two directions is dx and dy respectively, let t=|dx-dy |, if t is greater than the specified threshold, then set the se...
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