Title :
Vertex data compression through vector quantization
Author :
Chou, Peter H. ; Meng, Teresa H.
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
Abstract :
Rendering geometrically detailed 3D models requires the transfer and processing of large amounts of triangle and vertex geometry data. Compressing the geometry bit stream can reduce bandwidth requirements and alleviate transmission bottlenecks. In this paper, we show vector quantization to be an effective compression technique for triangle mesh vertex data. We present predictive vector quantization methods using unstructured code books as well as a product code pyramid vector quantizer. The technique is compatible with most existing mesh connectivity encoding schemes and does not require the use of entropy coding. In addition to compression, our vector quantization scheme can be used for complexity reduction by accelerating the computation of linear vertex transformations. Consequently, an encoded set of vertices can be both decoded and transformed in approximately 60 percent of the time required by a conventional method without compression
Keywords :
computational geometry; data compression; encoding; image coding; solid modelling; vector quantisation; 3D models; complexity reduction; computer graphics; data compression; encoding; geometry compression; product code pyramid vector quantizer; triangle mesh vertex data; unstructured code books; vector quantization; Acceleration; Bandwidth; Books; Data compression; Encoding; Entropy coding; Geometry; Product codes; Solid modeling; Vector quantization;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2002.1044522