Title :
An Algorithm of Extracting Features from Point Set Models
Author :
Pang, Xu-Fang ; Pang, Ming-Yong
Author_Institution :
Dept. of Educ. Technol., Nanjing Normal Univ., Nanjing, China
Abstract :
Our feature extraction is a multi-step refinement method, we use principle curvatures to flag potential feature points and develop a new approach to detect potential feature curves by employing our improved weight sensitive moving least squares. Then the potential feature points are enhanced by projecting onto the local potential feature curves. Using an optimized principal covariance analysis approach, we smooth the projected points. Finally smooth feature curves are obtained after resolving gaps and relaxing the results.
Keywords :
computational geometry; covariance analysis; feature extraction; iterative methods; feature extraction; multistep refinement method; point set model; principal covariance analysis; principle curvature; Clouds; Computer vision; Educational technology; Feature extraction; Least squares approximation; Least squares methods; Multilevel systems; Polynomials; Robustness; Surface fitting;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5366636
