Electronic Design

Wavelet Algorithm Provides Efficient Geometric-Data Compression

Led by CalTech computer science professor Peter Schröder and Wim Sweldens of Bell Labs' Mathematical Sciences Research Center, scientists have developed an algorithm that enables practical transmission of 3D data over the Internet as well as the ability to work with this kind of data on PCs. This algorithm for digital geometry compression allows the transmission of data concerning the size and shape with which 3D objects can be displayed, measured, and manipulated.

Usually, digital geometric data is acquired through a 3D laser scanner. This data represents objects using dense meshes of millions or even billions of triangles. The challenge in geometric compression is to use the fewest possible bits to store and transmit complex data sets.

The researchers report that their technique is 12 times more efficient than the method standardized in MPEG4 applications, as well as six times more efficient than the best previously published method. This algorithm is the first to use the premise of wavelet transformation, or "wavelets," in digital processing geometry. Wavelet transformation is a complement of Fourier transforms, long-established techniques for processing signals and analyzing physical data.

Prior to engaging in the current research, Sweldens developed a technique called "lifting" to generate wavelets without Fourier transforms. This method lets the wavelets better handle the geometry of curved surfaces. The researchers also eliminated coordinates that contributed little to quality while consuming a number of bits. Additionally, the team used "subdivision," a novel technique of building smooth surfaces, in developing the method.

This algorithm may be applied to solve current problems in many areas of geometry processing technology, including data acquisition by 3D scanning, noise removal, storage, transmission, authentication, editing, and reproduction. According to the researchers, producers of animated films and video games are expected to be the first to adopt wavelet-based geometry compression. Mass customization, as in clothing manufacture, is another likely use.

For more information, point your browser to www.eas.caltech.edu.

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