This paper provides the construction of statistical shape model based on elliptic Fourier transformation and minimum description length (MDL). The method does not require manual identification of landmarks on training shapes. Each training shapes can be decomposed into a set of ellipse by elliptic Fourier transformation at a different frequency level. The MDL objective function is based on elliptic Fourier descriptors and principal component analysis (EF-PCA). Experiments show that our method can get better models. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Wang, S., Qi, F., & Li, H. (2006). Minimum description length shape model based on elliptic fourier descriptors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 646–651). Springer Verlag. https://doi.org/10.1007/11760023_95
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