TECNOLOGIE PER LA RIABILITAZIONE. lezione # 5 la cattura del movimento. Both movement and morphology are represented. t k. t 3. t 2.

Size: px
Start display at page:

Download "TECNOLOGIE PER LA RIABILITAZIONE. lezione # 5 la cattura del movimento. Both movement and morphology are represented. t k. t 3. t 2."

Transcription

1 TENOLOGIE PER L RIILITZIONE Università dei Studi di Napoi "Federico II Facotà di Ineneria orso di Laurea in Ineneria iomedica oth movement and morphooy are represented the movement requires time variant information about the pose the morphooy may be time-invariant t 3 t t t 2 1 ezione # 5 a cattura de movimento... Prof. ureio appozzo Dipartimento di Scienze de Movimento Umano e deo Sport Laboratorio di ioineneria Istituto Universitario di Scienze Motorie - Roma dismus a cattura de movimento 1 Let s separate the two probems!! dismus a cattura de movimento 2 Data coection movement data acquisition/estimation (variabes) anatomica data acquisition/estimation (parameters) Data coection movement data acquisition/estimation (variabes) t 1 t 2 t 3 t t 1 t 2 t 3 t dismus a cattura de movimento 3 dismus a cattura de movimento 4 1

2 The description of the pose The term pose audes to the ocation in space of a body The description of the pose In order to describe the pose of the bone, we substitute a compex morphooy with a simpe and time invariant morphooy (riid body hypothesis) dismus a cattura de movimento 5 dismus a cattura de movimento 6 The description of the pose Motion capture In order to describe the pose of the bone, we substitute a compex morphooy with a simpe and time invariant morphooy (riid body hypothesis) Goba system of reference (Goba frame) z For each bone invoved in the anaysis, and in each samped instant of time, motion capture provides two vectors, i.e., six scaar quantities t O t j [ t t t ]; j 1,..., xj position vector yj zj z Loca system of reference (Loca frame) dismus a cattura de movimento 7 orientation vector [ θ θ ]; j 1,..., dismus a cattura de movimento 8 j θ This is, normay, done in an indirect fashion xj yj zj 2

3 Estimate of the instantaneous bone pose usin Stereophotorammetry the reconstructed instantaneous position of marers Given a point in motion in the 3-D aboratory space (marer), stereophotorammetry provides its position vector (three artesian coordinates - X, Y, Z) in each samped instant of time. Minima set up: three non-ained marers [ Y position vectors pij pxij pyij ] pzij ; i 1,...,c ; j 1,..., position vector [ t j t xj j [ t yj ] t zj ; j 1,..., θ xj θ yj X Z orientation vector θzj ]; j 1,..., dismus a cattura de movimento 9 dismus a cattura de movimento 10 amera Stereophotorammetry Given a point in motion in the 3-D aboratory space (marer), stereophotorammetry provides its position vector Principa pane (three artesian coordinates - X, Y, Z) in each samped instant of time. Noda point (N) Optica axis dismus a cattura de movimento 11 dismus a cattura de movimento 12 3

4 amera and object point amera and object point Principa pane Principa pane Noda point (N) Noda point (N) Optica axis Optica axis Object point Object point dismus a cattura de movimento 13 dismus a cattura de movimento 14 amera, object and imae points Imae point Imae point Principa pane Noda point (N) Optica axis Object point chip D Imae pane dismus a cattura de movimento 15 dismus a cattura de movimento 16 4

5 Stereophotorammetry Stereophotorammetry recordin phase N 1 P N 1 P N 2 N 2 dismus a cattura de movimento 17 dismus a cattura de movimento 18 Stereophotorammetry recordin phase Stereophotorammetry recordin phase N 1 P N 1 P N 2 N 2 dismus a cattura de movimento 19 dismus a cattura de movimento 20 5

6 Stereophotorammetry reconstruction phase Stereophotorammetry reconstruction phase N 1 P N 1 P N 2 N 2 dismus a cattura de movimento 21 dismus a cattura de movimento 22 Stereophotorammetry reconstruction phase (with errors) Stereophotorammetry reconstruction phase N 1 P N 1 P N 2 N 2 Object point position reconstruction has been achieved by usin the foowin information: Goba camera position and orientation Loca position of the noda points caibration parameters (time invariant) Loca position of the imae points measured variabe (time variant) dismus a cattura de movimento 23 dismus a cattura de movimento 24 6

7 naytica stereophotorammetry Position and orientation of a camera y aibration parameters x N z Measured variabes Mathematica mode Object point oba coordinates dismus a cattura de movimento 25 dismus a cattura de movimento 26 Position and orientation of a camera Position and orientation of a camera y θ p parameters y θ p parameters x p p (3 numbers) x p p (3 numbers) N θ p (3 numbers) N θ p (3 numbers) z d z d (1 number) p p p p dismus a cattura de movimento 27 dismus a cattura de movimento 28 7

8 Imae coordinates naytica stereophotorammetry y data x x p x p y p N y p p p1, θ p1, d 1, p p2, q p2, d 2 z x p1, y p1, x p2, y p2 Mathematica mode X, Y, Z dismus a cattura de movimento 29 dismus a cattura de movimento 30 System caibration aibration object The contro points (marers) are ocated in nown positions. The system of reference with respect to which their ocation is iven becomes the stereophotorammetric oba frame. p p1, θ p1, d 1, p p2, q p2, d 2 Y x p1, y p1, x p2, y p2 Mathematica mode X, Y, Z X dismus a cattura de movimento 31 Z dismus a cattura de movimento 32 8

9 aibration object So named dynamic caibration fter a first approximation caibration usin a simpe and stationary caibration object, the marers mounted on a riid wand are traced whie movin within the measurement voume. aibration parameters are iterativey modified whie optimizin an objective function. Y ourtesy of NIH Z X dismus a cattura de movimento 33 dismus a cattura de movimento 34 So named dynamic caibration System caibration p p1, θ p1, d 1, p p2, q p2, d 2 x p1, y p1, x p2, y p2 Mathematica mode X, Y, Z ourtesy of NIH dismus a cattura de movimento 35 dismus a cattura de movimento 36 9

10 The experiment ctive marers In each samped instant of time p p1, θ p1, d 1, p p2, q p2, d 2 x p1, y p1, x p2, y p2 Mathematica mode X, Y, Z dismus a cattura de movimento 37 dismus a cattura de movimento 38 The movement anaysis aboratory Marer trajectory reconstruction Determination of the instantaneous bone pose usin the reconstructed instantaneous position of marers? p dismus a cattura de movimento 39 p ij [ p p p ]; i 1,..., c; j 1,..., xij position vectors yij zij orientation vector [ θ θ ]; j 1,..., dismus a cattura de movimento 40 j t j position vector [ t t t ]; j 1,..., xj θ xj yj yj zj zj 10

11 simpe exampe Determination of the pose of a oca set of axes the position vectors or three non-ained marers are iven dismus a cattura de movimento 41 dismus a cattura de movimento 42 Determination of the pose of a oca set of axes Determination of the pose of a oca set of axes z 1. Definition of a pane 2. Definition of two orthoona axes on that pane 3. The third axis is orthoona to the former two axes dismus a cattura de movimento Definition of a pane 2. Definition of two orthoona axes in that pane 3. The third axis is orthoona to the former two axes dismus a cattura de movimento 44 11

12 Determination of the pose of a oca set of axes Determination of the instantaneous bone pose usin the reconstructed instantaneous position of marers y c ppendix z 1. Definition of a pane 2. Definition of two orthoona axes on that pane 3. The third axis is orthoona to the former two axes dismus a cattura de movimento 45 This oca frame is referred to as marer-custer technica frame dismus a cattura de movimento 46 Determination of the poses of the marer-custer technica frames y c Determination of the poses of the marer-custer technica frames y c Minima set up: three non-ained marers y c Redundant set up y c y 3 mathematica operator yc y >3 mathematica operator yc x x z z p ij [ p p p ]; i 1,..., c; j 1,..., xij position vectors yij zij cj orientation vector [ θ θ ]; j 1,..., dismus a cattura de movimento 47 t cj position vector [ t t t ]; j 1,..., cxj θ cxj cyj cyj czj czj p ij [ p p p ]; i 1,..., c; j 1,..., xij position vectors yij zij cj orientation vector [ θ θ ]; j 1,..., dismus a cattura de movimento 48 t cj position vector [ t t t ]; j 1,..., cxj θ cxj cyj cyj czj czj 12

13 Determination of the poses of the marer-custer technica frames y c Redundant set up y >3 mathematica operator y c yc fine dea ezione # 5 x z p ij [ p p p ]; i 1,..., c; j 1,..., xij position vectors yij zij cj [ t t t ]; j 1,..., orientation matrix R ; j 1,..., dismus a cattura de movimento 49 t position vector cxj cj cyj czj dismus a cattura de movimento 50 TENOLOGIE PER L RIILITZIONE The riid body Università dei Studi di Napoi "Federico II Facotà di Ineneria orso di Laurea in Ineneria iomedica ppendix riid-body pose determination y Prof. ureio appozzo Dipartimento di Scienze de Movimento Umano e deo Sport Laboratorio di ioineneria x Istituto Universitario di Scienze Motorie - Roma dismus a cattura de movimento 51 z dismus a cattura de movimento 52 13

14 Point position vectors Frame unity vectors determination y p p p y p p j j ( p p ) p p x x z dismus a cattura de movimento 53 z dismus a cattura de movimento 54 Frame unity vectors determination Frame unity vectors determination y p p p j i i ( p p ) j ( p p ) j y z j i i j x x z dismus a cattura de movimento 55 z dismus a cattura de movimento 56 14

15 Frame orientation-matrix and position vector determination Frame orientation-matrix and direction cosines R i j y p z x j i R t i j p c z y z j x i i xx yx zx x R y z j x x x xy yy zy xy yy zy xz yz zz xz yz zz z dismus a cattura de movimento 57 dismus a cattura de movimento 58 Frame orientation-vector determination Reationship between orientation matrix and orientation vector x y z x zy zz x xy xz R x yy yz [ ] θx θy θz xa ya z a xb zayb zazb xb xayb xazb a a a a a R b x b yay b yaz [ ] b b θbx θby θbz Given two frames a and b y z j i x z dismus a cattura de movimento 59 a b tn θ θ 2sinθ θ θ 2sinθ θ θ 2sinθ a bx a by a bz \ [( ) + ( ) + ( ) ] zayb ( ) zayb ( ) xazb ( ) yaxb yazb yazb zaxb xayb xaxb xazb + dismus a cattura de movimento 60 yayb zaxb + zazb 1 yaxb xayb

16 In summary In summary Given the marer position vectors in the oba frame: p p p The orientation of a riid body can therefore be described by a position vector y p z p p We were abe to estimate the position and orientation vectors of the oca frame (marer custer frame): t c c [ tcx tcy tcz] [ θ θ θ ] cx cy cz y z c or by an orientation matrix R z x In addition, the orientation matrix has been presented and its reationship with the orientation vector found. dismus a cattura de movimento 61 z x dismus a cattura de movimento 62 The end of ppendix dismus a cattura de movimento 63 16

TECNOLOGIE PER LA RIABILITAZIONE. lezione # 4 il movimento digitale. The representation of a bone using a cloud of points. René Descartes ( )

TECNOLOGIE PER LA RIABILITAZIONE. lezione # 4 il movimento digitale. The representation of a bone using a cloud of points. René Descartes ( ) TECNOLOGIE PER LA RIABILITAZIONE The representation of a bone usin a coud of points AA 2-26 Università dei Studi di Napoi "Federico II Corso di Laurea in Ineneria Biomedica Facotà di Ineneria ezione #

More information

Quaternion properties: addition. Introduction to quaternions. Quaternion properties: multiplication. Derivation of multiplication

Quaternion properties: addition. Introduction to quaternions. Quaternion properties: multiplication. Derivation of multiplication Introduction to quaternions Definition: A quaternion q consists of a scalar part s, s, and a vector part v ( xyz,,, v 3 : q where, [ s, v q [ s, ( xyz,, q s+ ix + jy + kz i 2 j 2 k 2 1 ij ji k k Quaternion

More information

5200/7200 Fall 2007 Concurrence theorems for triangles

5200/7200 Fall 2007 Concurrence theorems for triangles 5200/7200 Fall 2007 Concurrence theorems for triangles There are two basic concurrence theorems for triangles that hold in neutral geometry, that of medians and of angle bisectors, but it seems hard to

More information

If the center of the sphere is the origin the the equation is. x y z 2ux 2vy 2wz d 0 -(2)

If the center of the sphere is the origin the the equation is. x y z 2ux 2vy 2wz d 0 -(2) Sphere Definition: A sphere is the locus of a point which remains at a constant distance from a fixed point. The fixed point is called the centre and the constant distance is the radius of the sphere.

More information

Minima, Maxima, Saddle points

Minima, Maxima, Saddle points Minima, Maxima, Saddle points Levent Kandiller Industrial Engineering Department Çankaya University, Turkey Minima, Maxima, Saddle points p./9 Scalar Functions Let us remember the properties for maxima,

More information

Vector Calculus: Understanding the Cross Product

Vector Calculus: Understanding the Cross Product University of Babylon College of Engineering Mechanical Engineering Dept. Subject : Mathematics III Class : 2 nd year - first semester Date: / 10 / 2016 2016 \ 2017 Vector Calculus: Understanding the Cross

More information

Dipartimento di Elettronica, Informazione e Bioingegneria Robotics

Dipartimento di Elettronica, Informazione e Bioingegneria Robotics Dipartimento di Eettronica, Informazione e Bioingegneria Robotics Basic mechanica definitions @ 015 1 - mechanics subsystem MECHANICS (arm, whees, ) subsystem PROCESS (task, environment) Mobiity degrees

More information

Animating orientation. CS 448D: Character Animation Prof. Vladlen Koltun Stanford University

Animating orientation. CS 448D: Character Animation Prof. Vladlen Koltun Stanford University Animating orientation CS 448D: Character Animation Prof. Vladlen Koltun Stanford University Orientation in the plane θ (cos θ, sin θ) ) R θ ( x y = sin θ ( cos θ sin θ )( x y ) cos θ Refresher: Homogenous

More information

the remaiis c p i j fi r a lent'tli of time, can havetspeclii and case any affi :er shall refuse" or neglect <to «J3,b.01Jllis p. m.

the remaiis c p i j fi r a lent'tli of time, can havetspeclii and case any affi :er shall refuse or neglect <to «J3,b.01Jllis p. m. C «? G «C YY «C C C C C C G z «q Y C G «C Q «q C& qc C q q 6 «z C 6 6 «6 6 «} q % z Y 6 Y G Y & 6 Q q C«G C & C % G G 6 C 6 C 6 C q } 6 C 6 6 6 Q6 «G G q & q 6 C «C 6 G Y z666 «Y 66 ««6 «6? 6 «q q q «6?

More information

Absolute Scale Structure from Motion Using a Refractive Plate

Absolute Scale Structure from Motion Using a Refractive Plate Absolute Scale Structure from Motion Using a Refractive Plate Akira Shibata, Hiromitsu Fujii, Atsushi Yamashita and Hajime Asama Abstract Three-dimensional (3D) measurement methods are becoming more and

More information

CHICAGO, A P R I L

CHICAGO, A P R I L j v v ) ; ) ) b b F F F F x v bj Y Y K Q Y : 79 29 393 7 0 Y b - j bb b v- * bv b - b b b j b b b b v b b v b b v b * v K j v v b ; - v 8 - bj v - b b v v v v? v v * v b» j»q v- XY! b v b b v b x q b b

More information

-t:ma. u V:. 1! *VV; jf >*4: t i f n - v i ' ONABI E :VISITd:Rs ; 8 A EASTBOURNE, SAT. 5? -tesiste- COLLEGE. D ressm aker.

-t:ma. u V:. 1! *VV; jf >*4: t i f n - v i ' ONABI E :VISITd:Rs ; 8 A EASTBOURNE, SAT. 5? -tesiste- COLLEGE. D ressm aker. \ [ «* 33 3 5 «*» \ *? ^V- *VV >*4 J & & V! V Q Y x - X 8 - - 5 ( J 8 V Y X^ * V * V * ( ) ( --------- x () x J ( * -) V - V Y Y 8! -) Y Y Y8 ( - ) > Y - 8 Y - x x -- x ( ) 7 6 3 - Q V 4 6 8 V

More information

Section 4.2 selected answers Math 131 Multivariate Calculus D Joyce, Spring 2014

Section 4.2 selected answers Math 131 Multivariate Calculus D Joyce, Spring 2014 4. Determine the nature of the critical points of Section 4. selected answers Math 11 Multivariate Calculus D Joyce, Spring 014 Exercises from section 4.: 6, 1 16.. Determine the nature of the critical

More information

Animation Curves and Splines 2

Animation Curves and Splines 2 Animation Curves and Splines 2 Animation Homework Set up Thursday a simple avatar E.g. cube/sphere (or square/circle if 2D) Specify some key frames (positions/orientations) Associate Animation a time with

More information

3.1 Iterated Partial Derivatives

3.1 Iterated Partial Derivatives 3.1 Iterated Partial Derivatives Prof. Tesler Math 20C Fall 2018 Prof. Tesler 3.1 Iterated Partial Derivatives Math 20C / Fall 2018 1 / 19 Higher Derivatives Take the partial derivative of f (x, y) = x

More information

Sensor fusion for motion processing and visualization

Sensor fusion for motion processing and visualization Sensor fusion for motion processing and visualization Ali Baharev, PhD TÁMOP 4.2.2 Szenzorhálózat alapú adatgyűjtés és információfeldolgozás workshop April 1, 2011 Budapest, Hungary What we have - Shimmer

More information

In-plane principal stress output in DIANA

In-plane principal stress output in DIANA analys: linear static. class: large. constr: suppor. elemen: hx24l solid tp18l. load: edge elemen force node. materi: elasti isotro. option: direct. result: cauchy displa princi stress total. In-plane

More information

Relative Positioning from Model Indexing

Relative Positioning from Model Indexing Reative Positioning from Mode Indexing Stefan Carsson Computationa Vision and Active Perception Laboratory (CVAP)* Roya Institute of Technoogy (KTH), Stockhom, Sweden Abstract We show how to determine

More information

Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives

Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives In general, if f is a function of two variables x and y, suppose we let only x vary while keeping y fixed, say y = b, where b is a constant. By the definition of a derivative, we have Then we are really

More information

Interactive Computer Graphics. Hearn & Baker, chapter D transforms Hearn & Baker, chapter 5. Aliasing and Anti-Aliasing

Interactive Computer Graphics. Hearn & Baker, chapter D transforms Hearn & Baker, chapter 5. Aliasing and Anti-Aliasing Interactive Computer Graphics Aliasing and Anti-Aliasing Hearn & Baker, chapter 4-7 D transforms Hearn & Baker, chapter 5 Aliasing and Anti-Aliasing Problem: jaggies Also known as aliasing. It results

More information

Hw 4 Due Feb 22. D(fg) x y z (

Hw 4 Due Feb 22. D(fg) x y z ( Hw 4 Due Feb 22 2.2 Exercise 7,8,10,12,15,18,28,35,36,46 2.3 Exercise 3,11,39,40,47(b) 2.4 Exercise 6,7 Use both the direct method and product rule to calculate where f(x, y, z) = 3x, g(x, y, z) = ( 1

More information

DAY,.JANUARY 5, 1918 s.:i. A a T B O D B H « gg P li. SO UTH ST R E ET. BOY S A R B T A K E N FR O M T H E A G E O F E IG H T. i I..

DAY,.JANUARY 5, 1918 s.:i. A a T B O D B H « gg P li. SO UTH ST R E ET. BOY S A R B T A K E N FR O M T H E A G E O F E IG H T. i I.. ~~ * b ( : 3 5 0 BB Y Y 5 98 : : : ~ ~ : B B «8 B Y y < b / q b* x bb y :» > < ( q y x : K y b x y x x» b B y ^ 8 y Bx 3: ( ^ ^ 2* >? x 5 2 ^ Y ky Y b b B B B ( y ) B B ( ) B B B BK " B y Bkk / 2 B 5 y

More information

Structure from Motion. Prof. Marco Marcon

Structure from Motion. Prof. Marco Marcon Structure from Motion Prof. Marco Marcon Summing-up 2 Stereo is the most powerful clue for determining the structure of a scene Another important clue is the relative motion between the scene and (mono)

More information

Boolean Algebra. P1. The OR operation is closed for all x, y B x + y B

Boolean Algebra. P1. The OR operation is closed for all x, y B x + y B Boolean Algebra A Boolean Algebra is a mathematical system consisting of a set of elements B, two binary operations OR (+) and AND ( ), a unary operation NOT ('), an equality sign (=) to indicate equivalence

More information

Measurement Equipment. I. Introduction

Measurement Equipment. I. Introduction Least Squares Accelerometer Calibration in Precision Measurement Equipment Paige Thielen, ME535 Spring 2018 Abstract Various methods of accelerometer calibration can be used to increase the precision of

More information

(1) Given the following system of linear equations, which depends on a parameter a R, 3x y + 5z = 2 4x + y + (a 2 14)z = a + 2

(1) Given the following system of linear equations, which depends on a parameter a R, 3x y + 5z = 2 4x + y + (a 2 14)z = a + 2 (1 Given the following system of linear equations, which depends on a parameter a R, x + 2y 3z = 4 3x y + 5z = 2 4x + y + (a 2 14z = a + 2 (a Classify the system of equations depending on the values of

More information

OPENRAVE TUTORIAL. Robot Autonomy Spring 2014

OPENRAVE TUTORIAL. Robot Autonomy Spring 2014 OPENRAVE TUTORIAL Robot Autonomy Spring 2014 OPENRAVE Stands for: Open Robotics Automation Virtual Environment All-in-one Robotics Package Contains: Kinematics (forward, inverse, velocity, etc.) Collision

More information

.ps11 INTERPRETATION OF IMAGE FLOW: A SPATIO-TEMPORAL APPROACH. Muralidhara Subbarao. Abstract

.ps11 INTERPRETATION OF IMAGE FLOW: A SPATIO-TEMPORAL APPROACH. Muralidhara Subbarao. Abstract .ps11 INTERPRETATION OF IMAGE FLOW: A SPATIO-TEMPORAL APPROACH Muralidhara Subbarao Abstract Research on the interpretation of image flow (or optical flow) until now has mainly focused on instantaneous

More information

LOWELL WEEKLY JOURNAL

LOWELL WEEKLY JOURNAL Y $ b b Y b Y F Q Q Y 2 F {»» ( 2 Y b b b ] F F b / b b F q x x ) b Y b? F ( ) x _ q ( b b» ZZ F $ b b» b 6 2 q b x =2 2 6 2 b 2 2 bb b b? [ b q {» ( b b b ( x b $ b F b b q b b b q F b Y F b Y Y z b b

More information

Lecture outline Graphics and Interaction Scan Converting Polygons and Lines. Inside or outside a polygon? Scan conversion.

Lecture outline Graphics and Interaction Scan Converting Polygons and Lines. Inside or outside a polygon? Scan conversion. Lecture outine 433-324 Graphics and Interaction Scan Converting Poygons and Lines Department of Computer Science and Software Engineering The Introduction Scan conversion Scan-ine agorithm Edge coherence

More information

CS 231. Inverse Kinematics Intro to Motion Capture. 3D characters. Representation. 1) Skeleton Origin (root) Joint centers/ bones lengths

CS 231. Inverse Kinematics Intro to Motion Capture. 3D characters. Representation. 1) Skeleton Origin (root) Joint centers/ bones lengths CS Inverse Kinematics Intro to Motion Capture Representation D characters ) Skeeton Origin (root) Joint centers/ bones engths ) Keyframes Pos/Rot Root (x) Joint Anges (q) Kinematics study of static movement

More information

-LOWELL WEEI^LY JOURNAL.

-LOWELL WEEI^LY JOURNAL. Y c c $5 c C Y Y 7 %c > 7 5 > / ( c c C Y > c ( c C? x c C c c c q ~ 5 C () ) 5 5 $ 5 75 c c c c q< 5c xc c c > c c / c / c < c> C C 5 C [ c )c c 7 7 C / c c / C C CC C C

More information

Factoring. Factor: Change an addition expression into a multiplication expression.

Factoring. Factor: Change an addition expression into a multiplication expression. Factoring Factor: Change an addition expression into a multiplication expression. 1. Always look for a common factor a. immediately take it out to the front of the expression, take out all common factors

More information

Introduction to Computer Graphics. Modeling (3) April 27, 2017 Kenshi Takayama

Introduction to Computer Graphics. Modeling (3) April 27, 2017 Kenshi Takayama Introduction to Computer Graphics Modeling (3) April 27, 2017 Kenshi Takayama Solid modeling 2 Solid models Thin shapes represented by single polygons Unorientable Clear definition of inside & outside

More information

1.5 Equations of Lines and Planes in 3-D

1.5 Equations of Lines and Planes in 3-D 1.5. EQUATIONS OF LINES AND PLANES IN 3-D 55 Figure 1.16: Line through P 0 parallel to v 1.5 Equations of Lines and Planes in 3-D Recall that given a point P = (a, b, c), one can draw a vector from the

More information

21-256: Lagrange multipliers

21-256: Lagrange multipliers 21-256: Lagrange multipliers Clive Newstead, Thursday 12th June 2014 Lagrange multipliers give us a means of optimizing multivariate functions subject to a number of constraints on their variables. Problems

More information

(X 2,Y 2 ) (X 1,Y 1 ) (X 0,Y 0 ) (X c,y c ) (X 3,Y 3 )

(X 2,Y 2 ) (X 1,Y 1 ) (X 0,Y 0 ) (X c,y c ) (X 3,Y 3 ) Application Note Nov-2004 Probing for Dimensional Analysis This example shows how you can use Turbo PMAC s move-until-trigger function with the super-fast hardware position capture to find the exact location

More information

Section 1.8. Simplifying Expressions

Section 1.8. Simplifying Expressions Section 1.8 Simplifying Expressions But, first Commutative property: a + b = b + a; a * b = b * a Associative property: (a + b) + c = a + (b + c) (a * b) * c = a * (b * c) Distributive property: a * (b

More information

7.3 3-D Notes Honors Precalculus Date: Adapted from 11.1 & 11.4

7.3 3-D Notes Honors Precalculus Date: Adapted from 11.1 & 11.4 73 3-D Notes Honors Precalculus Date: Adapted from 111 & 114 The Three-Variable Coordinate System I Cartesian Plane The familiar xy-coordinate system is used to represent pairs of numbers (ordered pairs

More information

f (Pijk ) V. may form the Riemann sum: . Definition. The triple integral of f over the rectangular box B is defined to f (x, y, z) dv = lim

f (Pijk ) V. may form the Riemann sum: . Definition. The triple integral of f over the rectangular box B is defined to f (x, y, z) dv = lim Chapter 14 Multiple Integrals..1 Double Integrals, Iterated Integrals, Cross-sections.2 Double Integrals over more general regions, Definition, Evaluation of Double Integrals, Properties of Double Integrals.3

More information

Winter 2012 Math 255 Section 006. Problem Set 7

Winter 2012 Math 255 Section 006. Problem Set 7 Problem Set 7 1 a) Carry out the partials with respect to t and x, substitute and check b) Use separation of varibles, i.e. write as dx/x 2 = dt, integrate both sides and observe that the solution also

More information

Graphics and Interaction Transformation geometry and homogeneous coordinates

Graphics and Interaction Transformation geometry and homogeneous coordinates 433-324 Graphics and Interaction Transformation geometry and homogeneous coordinates Department of Computer Science and Software Engineering The Lecture outline Introduction Vectors and matrices Translation

More information

COMP30019 Graphics and Interaction Transformation geometry and homogeneous coordinates

COMP30019 Graphics and Interaction Transformation geometry and homogeneous coordinates COMP30019 Graphics and Interaction Transformation geometry and homogeneous coordinates Department of Computer Science and Software Engineering The Lecture outline Introduction Vectors and matrices Translation

More information

extracted occurring from the spatial and temporal changes in an image sequence. An image sequence

extracted occurring from the spatial and temporal changes in an image sequence. An image sequence Motion: Introduction are interested in the visual information that can be We from the spatial and temporal changes extracted in an image sequence. An image sequence occurring of a series of images (frames)

More information

Data Association for SLAM

Data Association for SLAM CALIFORNIA INSTITUTE OF TECHNOLOGY ME/CS 132a, Winter 2011 Lab #2 Due: Mar 10th, 2011 Part I Data Association for SLAM 1 Introduction For this part, you will experiment with a simulation of an EKF SLAM

More information

3.3 Optimizing Functions of Several Variables 3.4 Lagrange Multipliers

3.3 Optimizing Functions of Several Variables 3.4 Lagrange Multipliers 3.3 Optimizing Functions of Several Variables 3.4 Lagrange Multipliers Prof. Tesler Math 20C Fall 2018 Prof. Tesler 3.3 3.4 Optimization Math 20C / Fall 2018 1 / 56 Optimizing y = f (x) In Math 20A, we

More information

You may know these...

You may know these... You may know these... Chapter 1: Multivariables Functions 1.1 Functions of Two Variables 1.1.1 Function representations 1.1. 3-D Coordinate System 1.1.3 Graph of two variable functions 1.1.4 Sketching

More information

Kinematics and dynamics analysis of micro-robot for surgical applications

Kinematics and dynamics analysis of micro-robot for surgical applications ISSN 1 746-7233, England, UK World Journal of Modelling and Simulation Vol. 5 (2009) No. 1, pp. 22-29 Kinematics and dynamics analysis of micro-robot for surgical applications Khaled Tawfik 1, Atef A.

More information

Dubna 2018: lines on cubic surfaces

Dubna 2018: lines on cubic surfaces Dubna 2018: lines on cubic surfaces Ivan Cheltsov 20th July 2018 Lecture 1: projective plane Complex plane Definition A line in C 2 is a subset that is given by ax + by + c = 0 for some complex numbers

More information

The Distributive Property and Expressions Understand how to use the Distributive Property to Clear Parenthesis

The Distributive Property and Expressions Understand how to use the Distributive Property to Clear Parenthesis Objective 1 The Distributive Property and Expressions Understand how to use the Distributive Property to Clear Parenthesis The Distributive Property The Distributive Property states that multiplication

More information

and A L T ( ) SOLO "It means a lot to the iner-i IS FOR FARM H O M E S v ^ r. ' 0 Iak, "" h i s ruujie which was begun in July of last ) a i,, Mr

and A L T ( ) SOLO It means a lot to the iner-i IS FOR FARM H O M E S v ^ r. ' 0 Iak,  h i s ruujie which was begun in July of last ) a i,, Mr OC < x ( ) OO O XXX O C Y Y 3 93 C Y O C Z - # - - C ( ( - C «O O O O ) O C O $3 x ( ; - x C 8? ( - - ~ > - -) - - ) x 8 z -{ ( $2)() 8 ) & x - - $55 -( (Z(< \ > - x $27 x ) 5 ) - 6 / -O > - X - x C >

More information

Available online at ScienceDirect. 6th CIRP International Conference on High Performance Cutting, HPC2014

Available online at   ScienceDirect. 6th CIRP International Conference on High Performance Cutting, HPC2014 Available online at www.sciencedirect.com ScienceDirect Procedia CIRP 14 ( 214 323 328 6th CIRP International Conference on High Performance Cutting, HPC214 A machining test to evaluate geometric errors

More information

Problem Grade Total

Problem Grade Total CS 101, Prof. Loftin: Final Exam, May 11, 2009 Name: All your work should be done on the pages provided. Scratch paper is available, but you should present everything which is to be graded on the pages

More information

Software correction of geometric errors for multiaxis

Software correction of geometric errors for multiaxis Journal of Physics: Conference Series PAPER OPEN ACCESS Software correction of geometric errors for multiaxis systems o cite this article: V eleshevskii and V Sokolov 2017 J. Phys.: Conf. Ser. 858 012037

More information

2 Second Derivatives. As we have seen, a function f (x, y) of two variables has four different partial derivatives: f xx. f yx. f x y.

2 Second Derivatives. As we have seen, a function f (x, y) of two variables has four different partial derivatives: f xx. f yx. f x y. 2 Second Derivatives As we have seen, a function f (x, y) of two variables has four different partial derivatives: (x, y), (x, y), f yx (x, y), (x, y) It is convenient to gather all four of these into

More information

Final Exam Review. Name: Class: Date: Short Answer

Final Exam Review. Name: Class: Date: Short Answer Name: Class: Date: ID: A Final Exam Review Short Answer 1. Find the distance between the sphere (x 1) + (y + 1) + z = 1 4 and the sphere (x 3) + (y + ) + (z + ) = 1. Find, a a + b, a b, a, and 3a + 4b

More information

. 1. Chain rules. Directional derivative. Gradient Vector Field. Most Rapid Increase. Implicit Function Theorem, Implicit Differentiation

. 1. Chain rules. Directional derivative. Gradient Vector Field. Most Rapid Increase. Implicit Function Theorem, Implicit Differentiation 1 Chain rules 2 Directional derivative 3 Gradient Vector Field 4 Most Rapid Increase 5 Implicit Function Theorem, Implicit Differentiation 6 Lagrange Multiplier 7 Second Derivative Test Theorem Suppose

More information

DOWN PLUNGE CROSS SECTIONS

DOWN PLUNGE CROSS SECTIONS GG303 Lab 7 10/6/10 1 DOWN PLUNGE CROSS SECTIONS I Main Topics A Cylindrical folds B Downplunge cross-section views C Apparent dip II Cylindrical folds A Surface of a cylindrical fold is parallel to a

More information

(1) Tangent Lines on Surfaces, (2) Partial Derivatives, (3) Notation and Higher Order Derivatives.

(1) Tangent Lines on Surfaces, (2) Partial Derivatives, (3) Notation and Higher Order Derivatives. Section 11.3 Partial Derivatives (1) Tangent Lines on Surfaces, (2) Partial Derivatives, (3) Notation and Higher Order Derivatives. MATH 127 (Section 11.3) Partial Derivatives The University of Kansas

More information

[Bharathi, 3(2): February, 2014] ISSN: Impact Factor: 1.852

[Bharathi, 3(2): February, 2014] ISSN: Impact Factor: 1.852 IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY Associators in the Nucleus of Antiflexible Rings DR. D. Bharathi *1, M. Hema Prasad 2 *1 Associate Professor, Department of Mathematics,

More information

Backing-up Fuzzy Control of a Truck-trailer Equipped with a Kingpin Sliding Mechanism

Backing-up Fuzzy Control of a Truck-trailer Equipped with a Kingpin Sliding Mechanism Backing-up Fuzzy Contro of a Truck-traier Equipped with a Kingpin Siding Mechanism G. Siamantas and S. Manesis Eectrica & Computer Engineering Dept., University of Patras, Patras, Greece gsiama@upatras.gr;stam.manesis@ece.upatras.gr

More information

HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis Fall 2008

HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis Fall 2008 MIT OpenCourseWare http://ocw.mit.edu HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis Fall 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.

More information

Section 13.5: Equations of Lines and Planes. 1 Objectives. 2 Assignments. 3 Lecture Notes

Section 13.5: Equations of Lines and Planes. 1 Objectives. 2 Assignments. 3 Lecture Notes Section 13.5: Equations of Lines and Planes 1 Objectives 1. Find vector, symmetric, or parametric equations for a line in space given two points on the line, given a point on the line and a vector parallel

More information

Transformations. Write three rules based on what you figured out above: To reflect across the y-axis. (x,y) To reflect across y=x.

Transformations. Write three rules based on what you figured out above: To reflect across the y-axis. (x,y) To reflect across y=x. Transformations Geometry 14.1 A transformation is a change in coordinates plotted on the plane. We will learn about four types of transformations on the plane: Translations, Reflections, Rotations, and

More information

Chapter 6. Curves and Surfaces. 6.1 Graphs as Surfaces

Chapter 6. Curves and Surfaces. 6.1 Graphs as Surfaces Chapter 6 Curves and Surfaces In Chapter 2 a plane is defined as the zero set of a linear function in R 3. It is expected a surface is the zero set of a differentiable function in R n. To motivate, graphs

More information

CS 445 / 645 Introduction to Computer Graphics. Lecture 21 Representing Rotations

CS 445 / 645 Introduction to Computer Graphics. Lecture 21 Representing Rotations CS 445 / 645 Introduction to Computer Graphics Lecture 21 Representing Rotations Parameterizing Rotations Straightforward in 2D A scalar, θ, represents rotation in plane More complicated in 3D Three scalars

More information

A few multilinear algebraic definitions I Inner product A, B = i,j,k a ijk b ijk Frobenius norm Contracted tensor products A F = A, A C = A, B 2,3 = A

A few multilinear algebraic definitions I Inner product A, B = i,j,k a ijk b ijk Frobenius norm Contracted tensor products A F = A, A C = A, B 2,3 = A Krylov-type methods and perturbation analysis Berkant Savas Department of Mathematics Linköping University Workshop on Tensor Approximation in High Dimension Hausdorff Institute for Mathematics, Universität

More information

EXTRA-CREDIT PROBLEMS ON SURFACES, MULTIVARIABLE FUNCTIONS AND PARTIAL DERIVATIVES

EXTRA-CREDIT PROBLEMS ON SURFACES, MULTIVARIABLE FUNCTIONS AND PARTIAL DERIVATIVES EXTRA-CREDIT PROBLEMS ON SURFACES, MULTIVARIABLE FUNCTIONS AND PARTIAL DERIVATIVES A. HAVENS These problems are for extra-credit, which is counted against lost points on quizzes or WebAssign. You do not

More information

ME5286 Robotics Spring 2014 Quiz 1 Solution. Total Points: 30

ME5286 Robotics Spring 2014 Quiz 1 Solution. Total Points: 30 Page 1 of 7 ME5286 Robotics Spring 2014 Quiz 1 Solution Total Points: 30 (Note images from original quiz are not included to save paper/ space. Please see the original quiz for additional information and

More information

7.3 FIRST INVERSE ANTECEDENT BAF(BAF) OPERATION

7.3 FIRST INVERSE ANTECEDENT BAF(BAF) OPERATION 7.3 FIRST INVERSE ANTECEDENT BAFBAF OPERATION The inverse of the problem of the Direct BAFBAF Operation of the precedent Sections, could be also considered as a problem of Boolean Equations. Thus, if we

More information

GEOMETRIC TRANSFORMATIONS AND VIEWING

GEOMETRIC TRANSFORMATIONS AND VIEWING GEOMETRIC TRANSFORMATIONS AND VIEWING 2D and 3D 1/44 2D TRANSFORMATIONS HOMOGENIZED Transformation Scaling Rotation Translation Matrix s x s y cosθ sinθ sinθ cosθ 1 dx 1 dy These 3 transformations are

More information

Kinematic Model of Robot Manipulators

Kinematic Model of Robot Manipulators Kinematic Model of Robot Manipulators Claudio Melchiorri Dipartimento di Ingegneria dell Energia Elettrica e dell Informazione (DEI) Università di Bologna email: claudio.melchiorri@unibo.it C. Melchiorri

More information

= w. w u. u ; u + w. x x. z z. y y. v + w. . Remark. The formula stated above is very important in the theory of. surface integral.

= w. w u. u ; u + w. x x. z z. y y. v + w. . Remark. The formula stated above is very important in the theory of. surface integral. 1 Chain rules 2 Directional derivative 3 Gradient Vector Field 4 Most Rapid Increase 5 Implicit Function Theorem, Implicit Differentiation 6 Lagrange Multiplier 7 Second Derivative Test Theorem Suppose

More information

LOGIC CIRCUITS. Kirti P_Didital Design 1

LOGIC CIRCUITS. Kirti P_Didital Design 1 LOGIC CIRCUITS Kirti P_Didital Design 1 Introduction The digital system consists of two types of circuits, namely (i) Combinational circuits and (ii) Sequential circuit A combinational circuit consists

More information

Stereo. CS 510 May 2 nd, 2014

Stereo. CS 510 May 2 nd, 2014 Stereo CS 510 May 2 nd, 2014 Where are we? We are done! (essentiay) We covered image matching Correation & Correation Fiters Fourier Anaysis PCA We covered feature-based matching Bag of Features approach

More information

13.1. Functions of Several Variables. Introduction to Functions of Several Variables. Functions of Several Variables. Objectives. Example 1 Solution

13.1. Functions of Several Variables. Introduction to Functions of Several Variables. Functions of Several Variables. Objectives. Example 1 Solution 13 Functions of Several Variables 13.1 Introduction to Functions of Several Variables Copyright Cengage Learning. All rights reserved. Copyright Cengage Learning. All rights reserved. Objectives Understand

More information

Research on error detection technology of numerical control machine tool. Cao YongJie

Research on error detection technology of numerical control machine tool. Cao YongJie Joint International Mechanical, Electronic and Information Technology Conference (JIMET 2015) Research on error detection technology of numerical control machine tool Cao YongJie Shanghai University of

More information

Visual Recognition: Image Formation

Visual Recognition: Image Formation Visual Recognition: Image Formation Raquel Urtasun TTI Chicago Jan 5, 2012 Raquel Urtasun (TTI-C) Visual Recognition Jan 5, 2012 1 / 61 Today s lecture... Fundamentals of image formation You should know

More information

Definition 3.1 The partial derivatives of a function f(x, y) defined on an open domain containing (x, y) are denoted by f

Definition 3.1 The partial derivatives of a function f(x, y) defined on an open domain containing (x, y) are denoted by f Chapter 3 Draft October 3, 009 3. Partial Derivatives Overview: Partial derivatives are defined by differentiation in one variable, viewing all others as constant (frozen at some value). The reduction

More information

521493S Computer Graphics Exercise 2 Solution (Chapters 4-5)

521493S Computer Graphics Exercise 2 Solution (Chapters 4-5) 5493S Computer Graphics Exercise Solution (Chapters 4-5). Given two nonparallel, three-dimensional vectors u and v, how can we form an orthogonal coordinate system in which u is one of the basis vectors?

More information

Working with Algebraic Expressions

Working with Algebraic Expressions 2 Working with Algebraic Expressions This chapter contains 25 algebraic expressions; each can contain up to five variables. Remember that a variable is just a letter that represents a number in a mathematical

More information

Robot Inverse Kinematics Asanga Ratnaweera Department of Mechanical Engieering

Robot Inverse Kinematics Asanga Ratnaweera Department of Mechanical Engieering PR 5 Robot Dynamics & Control /8/7 PR 5: Robot Dynamics & Control Robot Inverse Kinematics Asanga Ratnaweera Department of Mechanical Engieering The Inverse Kinematics The determination of all possible

More information

Chapter 15: Functions of Several Variables

Chapter 15: Functions of Several Variables Chapter 15: Functions of Several Variables Section 15.1 Elementary Examples a. Notation: Two Variables b. Example c. Notation: Three Variables d. Functions of Several Variables e. Examples from the Sciences

More information

Ray casting. Ray casting/ray tracing

Ray casting. Ray casting/ray tracing Ray casting Ray casting/ray tracing Iterate over pixels, not objects Effects that are difficult with Z-buffer, are easy with ray tracing: shadows, reflections, transparency, procedural textures and objects

More information

Linear First-Order PDEs

Linear First-Order PDEs MODULE 2: FIRST-ORDER PARTIAL DIFFERENTIAL EQUATIONS 9 Lecture 2 Linear First-Orer PDEs The most general first-orer linear PDE has the form a(x, y)z x + b(x, y)z y + c(x, y)z = (x, y), (1) where a, b,

More information

Response Surface Model Updating for Nonlinear Structures

Response Surface Model Updating for Nonlinear Structures Response Surface Mode Updating for Noninear Structures Gonaz Shahidi a, Shamim Pakzad b a PhD Student, Department of Civi and Environmenta Engineering, Lehigh University, ATLSS Engineering Research Center,

More information

Solution 2. ((3)(1) (2)(1), (4 3), (4)(2) (3)(3)) = (1, 1, 1) D u (f) = (6x + 2yz, 2y + 2xz, 2xy) (0,1,1) = = 4 14

Solution 2. ((3)(1) (2)(1), (4 3), (4)(2) (3)(3)) = (1, 1, 1) D u (f) = (6x + 2yz, 2y + 2xz, 2xy) (0,1,1) = = 4 14 Vector and Multivariable Calculus L Marizza A Bailey Practice Trimester Final Exam Name: Problem 1. To prepare for true/false and multiple choice: Compute the following (a) (4, 3) ( 3, 2) Solution 1. (4)(

More information

CS348B Lecture 2 Pat Hanrahan, Spring Greeks: Do light rays proceed from the eye to the light, or from the light to the eye?

CS348B Lecture 2 Pat Hanrahan, Spring Greeks: Do light rays proceed from the eye to the light, or from the light to the eye? Page 1 Ray Tracing Today Basic algorithms Overview of pbrt Ray-surface intersection for single surface Next lecture Acceleration techniques for ray tracing large numbers of geometric primitives Classic

More information

Math 240 Practice Problems

Math 240 Practice Problems Math 4 Practice Problems Note that a few of these questions are somewhat harder than questions on the final will be, but they will all help you practice the material from this semester. 1. Consider the

More information

Jacobian Range Space

Jacobian Range Space Kinematic Redundanc A manipuator ma have more DOFs than are necessar to contro a desired variabe What do ou do w/ the etra DOFs? However, even if the manipuator has enough DOFs, it ma sti be unabe to contro

More information

Research of Classification based on Deep Neural Network

Research of  Classification based on Deep Neural Network 2018 Internationa Conference on Sensor Network and Computer Engineering (ICSNCE 2018) Research of Emai Cassification based on Deep Neura Network Wang Yawen Schoo of Computer Science and Engineering Xi

More information

Z+z 1 X2 Y2. or y, Graph / 4 25 jj y=±x. x2+y 2=

Z+z 1 X2 Y2. or y, Graph / 4 25 jj y=±x. x2+y 2= Conic Sections Understanding the graphs of conic sections is made easier if you first begin with the simplest form of a conic section. These would be the graphs that are centered at the origin. If we can

More information

Motion Control (wheeled robots)

Motion Control (wheeled robots) Motion Control (wheeled robots) Requirements for Motion Control Kinematic / dynamic model of the robot Model of the interaction between the wheel and the ground Definition of required motion -> speed control,

More information

Fundamentals of Structural Geology Exercise: concepts from chapter 2

Fundamentals of Structural Geology Exercise: concepts from chapter 2 0B Reading: Fundamentals of Structural Geology, Ch 2 1) Develop a MATLAB script that plots the spherical datum (Fig. 2.1a) with unit radius as a wire-frame diagram using lines of constant latitude and

More information

(c) 0 (d) (a) 27 (b) (e) x 2 3x2

(c) 0 (d) (a) 27 (b) (e) x 2 3x2 1. Sarah the architect is designing a modern building. The base of the building is the region in the xy-plane bounded by x =, y =, and y = 3 x. The building itself has a height bounded between z = and

More information

Dynamic IBVS Control of an Underactuated UAV

Dynamic IBVS Control of an Underactuated UAV Proceedings of the 212 IEEE International Conference on Robotics and Biomimetics December 11-14, 212, Guangzhou, China Dynamic IBVS Control of an Underactuated UAV Hamed Jabbari 1,2, Giuseppe Oriolo 2

More information

CSE 167: Introduction to Computer Graphics Lecture #2: Coordinate Transformations

CSE 167: Introduction to Computer Graphics Lecture #2: Coordinate Transformations CSE 167: Introduction to Computer Graphics Lecture #2: Coordinate Transformations Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2013 Announcements Homework #1 due Friday Oct

More information

Sensitivity Analysis of Hopfield Neural Network in Classifying Natural RGB Color Space

Sensitivity Analysis of Hopfield Neural Network in Classifying Natural RGB Color Space Sensitivity Anaysis of Hopfied Neura Network in Cassifying Natura RGB Coor Space Department of Computer Science University of Sharjah UAE rsammouda@sharjah.ac.ae Abstract: - This paper presents a study

More information

Computation of the gravity gradient tensor due to topographic masses using tesseroids

Computation of the gravity gradient tensor due to topographic masses using tesseroids Computation of the gravity gradient tensor due to topographic masses using tesseroids Leonardo Uieda 1 Naomi Ussami 2 Carla F Braitenberg 3 1. Observatorio Nacional, Rio de Janeiro, Brazil 2. Universidade

More information

1.5 Equations of Lines and Planes in 3-D

1.5 Equations of Lines and Planes in 3-D 56 CHAPTER 1. VECTORS AND THE GEOMETRY OF SPACE Figure 1.16: Line through P 0 parallel to v 1.5 Equations of Lines and Planes in 3-D Recall that given a point P = (a, b, c), one can draw a vector from

More information