Abstract: A method models a three-dimensional object by first acquiring alpha mattes of the object for multiple viewpoints. The alpha mattes are then projected onto a surface hull completely enclosing the object to construct an opacity hull storing opacity values of the surface of the object. The object is illuminated for various lighting conditions while images are acquired. The images are projected onto the opacity hull to render the object under arbitrary lighting conditions for arbitrary viewpoints.

Abstract: A method models a three-dimensional object by first acquiring alpha mattes of the object for multiple viewpoints. The alpha mattes are then projected onto a surface hull completely enclosing the object to construct an opacity hull storing opacity values of the surface of the object. The object is illuminated for various lighting conditions while images are acquired. The images are projected onto the opacity hull to render the object under arbitrary lighting conditions for arbitrary viewpoints.

Abstract: A method models a three-dimensional object by first acquiring alpha mattes of the object for multiple viewpoints. The alpha mattes are then projected onto a surface hull completely enclosing the object to construct an opacity hull storing opacity values of the surface of the object. The object is illuminated for various lighting conditions while images are acquired. The images are projected onto the opacity hull to render the object under arbitrary lighting conditions for arbitrary viewpoints.

Abstract: A system digitizes a three-dimensional object as a three-dimension model by placing the object on a turntable while taking two sets of corresponding images. The first set of images and the second set of images are obtained while rotating the turntable to a various positions and illuminated the object with the overhead lights and backlights. There is a one to one correspondence for images in each set for each position of the turntable. Object shape data and texture data are respectively extracted from the first and second set of images. The object shape data is correlated with the object texture data to construct the three-dimensional digital model stored in a memory of a computer system.

Abstract: In a digital image processing system, a dedicated inverse discrete cosine transform (IDCT) processor comprising a controller and an array of accumulators is provided for performing n.times.n inverse discrete cosine transforms. The controller controls the computation of the output vector using a forward mapping procedure. The controller causes k unique kernel values of the reconstruction kernel of each non-zero transform domain coefficient to be selectively accumulated by the array of accumulators, where k equals at most (n.sup.2 +2n)/8. The array of accumulators comprises accumulator blocks sharing an input and a control line designed to exploit the symmetry characteristics of the reconstruction kernels. Each accumulator block is designed to perform a limited number of distinct operations. The accumulator blocks are logically grouped. P symmetry selection bits and less than an operation configuration selection bits, where 2.sup.q equals n.sup.

Abstract: In a digital image processing system, a CPU and a memory is provided to an image signal processing subsystem for computing the output vector of an inverse discrete cosine transform. The inverse discrete cosine transform is represented as a linear system and the output vector is computed using a forward mapping procedure where system matrix columns scaled by the non-zero quantized corresponding transform domain coefficient selected from the input vector are successively accumulated into the output vector. Dequantizations and scalings are performed as a combined single step by looking up the kernel values of the scaled reconstruction kernels from lookup tables corresponding to the selected transform domain coefficients' positions in the input vector. The lookup tables are highly optimized exploiting the symmetry characteristics of the reconstruction kernels, the inherent properties of quantization and the statistical attributes of the quantized transform domain coefficients.