Abstract: In recent days, applications using 3D models are increasing. Since the 3D model contains a huge amount of information, compression of the 3D model data is necessary for efficient storage or transmission. In this paper, we propose an adaptive encoding scheme to compress the geometry information of the 3D model. Using the Levinson-Durbin algorithm, the encoder first predicts vertex positions along a vertex spanning tree. After each prediction error is normalized, the prediction error vector of each vertex point is represented in the spherical coordinate system (r,$theta@,$phi@). Each r is then quantizes by an optimal uniform quantizer. A pair of each ($theta@,$phi@) is also successively encoded by partitioning the surface of the sphere according to the quantized value of r. The proposed scheme demonstrates improved coding efficiency by exploiting the statistical properties of r and ($theta@,$phi@). !8
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