Probability distribution of index distances in normal index array for normal vector compression

Authors:
Deok-Soo Kim;Youngsong Cho;Donguk Kim;Hyun Kim
Affiliations:
Department of Industrial Engineering, Hanyang University, Seoul, South Korea;Department of Industrial Engineering, Hanyang University, Seoul, South Korea;Department of Industrial Engineering, Hanyang University, Seoul, South Korea;Concurrent Engineering Research Team, Electronics and Telecommunications Research Institute, Daejeon, South Korea
Venue:
ICCS'03 Proceedings of the 1st international conference on Computational science: PartI
Year:
2003

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Abstract

Shape models are in these days frequently transmitted over Internet and the research of their compression has been started. Considering the large portion of shape model can be normal vectors, a new scheme was recently presented to compress normal vectors using clustering and mixed indexing scheme. Presented in this paper is a mathematical investigation of the scheme to analyze the probability distribution of normal index distances in Normal Index array which is critical for the compression. The probability distribution is formulated so that the values can be easily calculated once the relative probabilities of C, R, E, S, and L op-codes in Edgebreaker are known. It can be shown that the distribution of index distances can be easily transformed into a few measures for the compression performance of the proposed algorithm.