Shape from texture is best analyzed in two stages, analogous to steropsis and structure from motion: (a) Computing the `texture distortion'' from the image, and (b) Interpreting the `texture distortion'' to infer the orientation and shape of the surface in the scene. We model the texture distortion for a given point and direction on the image plane as an affine transformation and derive the relationship between the parameters of this transformation and the shape parameters. We have developed a technique for estimating affine transforms between nearby image patches which is based on solving a system of linear constraints derived from a differential analysis. One need not explicitly identify texels or make restrictive assumptions about the nature of the texture like isotropy. We use non- linear minimization of a least squares error criterion to recover the surface orientation (slant and tilt) and shape (principal curvatures and directions) based on the estimated affine transforms in a number of different directions. A simple linear algorithm based on singular value decomposition of the linear parts of the affine transforms provides the initial guess for the minimization procedure. Experimental results on both planar and curved surfaces under perspective projection demonstrate good estimates for both orientation and shape. A sensitivity analysis yields predictions for both computer vision algorithms and human perception of shape from texture.
Abstract In this chapter, we present our initial findings of the impact of policy on Internet paths. In particular, our findings reveal answers to the following questions: How does policy based routing inflate Internet paths? For a source-destination pair, does there exist a detour path and how good is the best detour path compared to the policy path? Does policy routing funnel Internet paths through larger autonomous systems (ASs).
We developed a method for processing roots from soil cores and monoliths in the laboratory to reduce the time and cost devoted to separating roots from debris and improve the accuracy of root variable estimates. The method was tested on soil cores from a California oak savanna, with roots from trees, Quercus douglasii, and annual grasses. In the randomized sampling method, one isolates the sample fraction consisting of roots and organic debris < = 1 cm in length, and randomizes it through immersion in water and vigorous mixing. Sub-samples from the mixture are then used to estimate the percentage of roots in this fraction, thereby enabling an estimate of total sample biomass. We found that root biomass estimates, determined through the randomization method, differed from total root biomass established by meticulously picking every root from a sample with an error of 3.0 % +/− 0.6 % s.e. This method greatly reduces the time and resources required for root processing from soil cores and monoliths, and improves the accuracy of root variable estimates compared to standard methods. This gives researchers the ability to increase sample frequency and reduce the error associated with studying roots at the landscape and plant scales.
Ultra-thin dendrimer films are effective resists for high-resolution lithography using a scanning probe. The authors describe dendritic monolayer formation via covalent attachment to a silicon wafer surface and the field-enhanced oxidation of the dendrimer monolayers using scanning probe lithography to create features with dimensions less than 60 nm. Poly-(benzyl ether) dendrimers, terminated with either benzyl or tert-butyldiphenylsilyl ether groups, were used because of their relative ease of preparation and derivatization.
The facile one-phase synthesis of N-heterocyclic carbene-stabilized gold nanoparticles (NHC-AuNP) by reduction of NHC-gold(I) complexes and their self-assembly into 3D superlattices is presented.