Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for rec...
Michael B. Wakin, Jason N. Laska, Marco F. Duarte,...
The 3D object recognition from a single or multiple 2D images is a very important problem in the computer vision field with a wide range of real applications. Considering the affi...
Classical linear wavelet representations of images have the drawback that they are not well-suited to represent edge information. To overcome this problem, nonlinear multiresoluti...
This paper presents a novel method for computing simulated x-ray images, or DRRs (digitally reconstructed radiographs), of tetrahedral meshes with higher-order attenuation functio...
Ofri Sadowsky, Jonathan D. Cohen, Russell H. Taylo...
We present a practical approach for surface reconstruction of smooth mirror-like objects using sparse reflection correspondences (RCs). Assuming finite object motion with a fix...