We present a new technique to jointly MIP-map BRDF and normal maps. Starting with generating an instant BRDF map, our technique builds its MIP-mapped versions based on a highly efficient algorithm that interpolates von Mises-Fisher (vMF) distributions. In our BRDF MIP-maps, each pixel stores a vMF mixture approximating the average of all BRDF lobes from the finest level. Our method is capable o...

This paper presents a novel architecture mapping technique which was essential in the design of a QR array which forms the core processor of a single chip adaptive beamforming system. The mapping technique assigns a QR triangular array of 2m+3m+1 cells down onto a linear architecture of m+1 processors. The mapping results in a linear systolic architecture with one hundred percent hardware utili...

We present an automatic method for mapping a system of linear recurrence equations onto systolic architectures. First, we show that systolic architectures can be derived from linear recurrence equations using the notion of directed recurrence equations. Next, we provide a procedure called CUBIZATION to achieve better performance while mapping such equations. The CUBIZATION procedure is complete...

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and lo...

In this paper, we describe a methodology for mapping normal linear recurrence equations onto a spectrum of systolic architectures. First, we provide a method to map a system of directed recurrence equations, a subclass of linear recurrence equations, onto a very general architecture referred to as basic systolic architecture and establish correctness of the implementation. We also show how eeci...

In this paper we establish a duality between boosting and SVM, and use this to derive a novel discriminant dimensionality reduction algorithm. In particular, using the multiclass formulation of boosting and SVM we note that both use a combination of mapping and linear classification to maximize the multiclass margin. In SVM this is implemented using a pre-defined mapping (induced by the kernel)...

comparison of the effect of concept mapping and nursing process on self-regulated learning, self-efficacy and cognitive strategies in nursing students     rezaei k [1] *, kouhestani h [2] , nejat n [3] , ebrahimi fakhar h [4]     received: 12 oct , 2011 accepted: 20 jan , 2012     abstract   background & aims : the success of nursing students depends on the understanding of complex concepts and...

Mapping techniques have been regularly used for visualization of high-dimensional data sets. In this paper, mapping to d 2 is studied, with the purpose of feature extraction. Two di erent non-linear techniques are studied: self-organizing maps and auto-associative feedforward networks. The non-linear techniques are compared to linear Principal Component Analysis (PCA). A comparison with respect...

Inconsistencies between a phylogenetic tree calculated from a set of related genes and known species phylogeny may be due to duplications events in the gene family under study. Tree Mapping attempts to pinpoint gene duplications in order to explain such discrepancies. The e ort in this explanation is measured using a tree mapping measure. Very little algorithmic work has so far been invested in...

A novel and computationally simple method is presented for triangulation of 3D points corresponding to the image coordinates in a pair of stereo images. The image points are described in terms of homogeneous coordinates which are jointly represented as the outer products of these homogeneous coordinates. This paper derives a linear transformation which maps the joint representation directly to ...