'Radial basis functions' diaporamas de présentation

Advanced Skin

Advanced Skin. CSE169: Computer Animation Instructor: Steve Rotenberg UCSD, Winter 2005. Shape Interpolation Algorithm. To compute a blended vertex position: The blended position is the base position plus a contribution from each target whose DOF value is greater than 0

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Morphing,

Morphing, . and. Warping. Blending. Cartographic Applications. Definition . Morphing is a special technique that creates a smooth, controlled transformation of one image into another. . Transforming Shape. Warping vs Morphing Warping Single object

918 views • 49 slides

Review

Review. CSE169: Computer Animation Instructor: Steve Rotenberg UCSD, Winter 2005. Character Animation. Rigging Skeleton Skinning Morphing (shape interpolation) DOF mapping Animation System Channels Animation player Blending State machines Motion capture Procedural Animation

556 views • 46 slides

Interpolation Methods

Interpolation Methods. Robert A. Dalrymple Johns Hopkins University. Why Interpolation?. For discrete models of continuous systems, we need the ability to interpolate values in between discrete points.

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Support Vector Machines and Kernel Methods

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Hands on training on developing ground water level map using geo-statistical analyst

Dr. A.K.M. Saiful Islam. Hands on training on developing ground water level map using geo-statistical analyst. Institute of Water and Flood Management (IWFM) Bangladesh University of Engineering and Technology (BUET). Geo-statistical Analyst of ArcGIS. This training will be on:

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Verbs and Adverbs: Multidimensional Motion Interpolation Using Radial Basis Functions

Verbs and Adverbs: Multidimensional Motion Interpolation Using Radial Basis Functions. Charles Rose. Bobby Bodenheimer. Michael F. Cohen. Presented by Sean Jellish. The Problem. Creating believable animated humans is hard Results are difficult to reuse

634 views • 25 slides

Kernel Methods Part 2

Kernel Methods Part 2. Bing Han June 26, 2008. Local Likelihood. Logistic Regression. Logistic Regression. After a simple calculation, we get We denote the probabilities Logistic regression models are usually fit by maximum likelihood. Local Likelihood.

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Approximation of heavy models using Radial Basis Functions

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Skeleton Extraction of 3D Objects by Radial Basis Functions for Content-based Retrieval in MPEG-7

Skeleton Extraction of 3D Objects by Radial Basis Functions for Content-based Retrieval in MPEG-7. Ming Ouhyoung Fu-Che Wu, Wan-Chun Ma, Communication and Multimedia Lab Dept. of Computer Science and Information Engineering, National Taiwan University. Previous Collaboration: MPEG-4 Based.

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Pattern Recognition and Machine Learning: Kernel Methods

Pattern Recognition and Machine Learning: Kernel Methods. Overview. Many linear parametric models can be recast into an equivalent dual representation in which the predictions are based on linear combinations of a kernel function evaluated at the training data points

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Surface Reconstruction using Radial Basis Functions

Surface Reconstruction using Radial Basis Functions. Michael Kunerth, Philipp Omenitsch and Georg Sperl. 1 Institute of Computer Graphics and Algorithms Vienna University of Technology. 2 <insert 2nd affiliation (institute) here> <insert 2nd affiliation (university) here>.

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Kriging - Introduction

Kriging - Introduction. Method invented in the 1950s by South African geologist Daniel Krige (1919-) for predicting distribution of minerals. Became very popular for fitting surrogates to expensive computer simulations in the 21 st century. It is one of the best surrogates available.

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Radial Basis Functions and Application in Edge Detection

Radial Basis Functions and Application in Edge Detection. Project by: Chris Cacciatore, Tian Jiang, and Kerenne Paul. Abstract.

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Local surrogates

Local surrogates. To model a complex wavy function we need a lot of data. Modeling a wavy function with high order polynomials is inherently ill-conditioned. With a lot of data we normally predict function values using only nearby values. We may fit several local surrogates as in figure.

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3D Analysis of Breast Changes for Medical Images

3D Analysis of Breast Changes for Medical Images. Lijuan Zhao Advisors: Prof. Fatima Merchant Prof. Shishir Shah. OUTLINE. Motivation Computational Problem Challenges Literature Review Future Work. Motivation. Breast Reconstruction

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Radial Basis Functions and Application in Edge Detection

Radial Basis Functions and Application in Edge Detection. Chris Catiatore , Tian Jiang and Kerenne Paul. Abstract.

221 views • 13 slides

???? ?? Introduction to Meshless Methods

???? ?? Introduction to Meshless Methods. Reporter : ??? Wen-Han, Tsai Date : 2013/08/15. Content. Introduction Radial B asis Functions (RBFs) Types of Meshless Methods Examples. Introduction - Why use meshless methods ?.

799 views • 12 slides

ANJUMAN ENGINEERING COLLEGE

ANJUMAN ENGINEERING COLLEGE. Department of Electrical & Electronics. Seminar Report. On. NEURAL NETWORKS IN PROCESS CONTROL. Guided by. Presented by. ASHIF RAHMATHULLA T.T. Mr.ANIL KADLE M.Tech.[I.E.]. ABSTRACT.

238 views • 5 slides