Multi-linear Systems for 3D-from-2D Interpretation. Lecture 1. Multi-view Geometry from a Stationary Scene. Amnon Shashua

Size: px
Start display at page:

Download "Multi-linear Systems for 3D-from-2D Interpretation. Lecture 1. Multi-view Geometry from a Stationary Scene. Amnon Shashua"

Transcription

1 Mult-lnea Sytem fo 3D-fom-D Inteetaton Lectue Mult-vew Geomety fom a Statonay Scene Amnon Shahua Hebew Unvety of Jeualem Iael U. of Mlano, Lectue : multvew

2 Mateal We Wll Cove oday he tuctue of 3D->D oecton matx A me on oectve geomety of the lane Eola Geomety and Fundamental Matx Why 3 vew? Pme on Covaant-Contavaant Index conventon focal eno Quadfocal eno U. of Mlano, Lectue : multvew

3 he tuctue of 3D->D oecton matx U. of Mlano, Lectue : multvew 3

4 U. of Mlano, Lectue : multvew 4 he Stuctue of a Poecton Matx W V U P w O t n b U V W X Y Z O OP OO + Ut + Vn + Wb R t n b [ ] X Y Z R U V W +

5 he Stuctue of a Poecton Matx x f X Z + x (,, f ( x, y ) ) y Z x P X X Y Z y f Y Z + y Y U. of Mlano, Lectue : multvew 5

6 U. of Mlano, Lectue : multvew 6 he Stuctue of a Poecton Matx x f X Z + x y f Y Z + y x y f x f y X Y Z K(RP w + ) K[R;] U V W P M 4 3

7 Geneally, he Stuctue of a Poecton Matx coθ f x f x nθ f K y nθ x y θ y x ( x, y ) called the ncle ont f x coθ nθ called the ew f y f x aect ato U. of Mlano, Lectue : multvew 7

8 Why c the camea cente? Conde the otcal ay MQ (λ ) λmp he Camea Cente M 3 4 P M ha an3, thu c uch that Mc MP All ont along the lne Q (λ ) ae maed to the ame ont Q ( λ ) λp + ( λ ) c P Q (λ ) a ay though the camea cente c U. of Mlano, Lectue : multvew 8

9 he Eola Pont c e M c e Mc c U. of Mlano, Lectue : multvew 9

10 Choce of Canoncal Fame MP MWW P M P M WW P W P the new wold coodnate fame We have 5 degee of feedom (6 uto cale) Chooe W uch that MW [ I ;] U. of Mlano, Lectue : multvew

11 Choce of Canoncal Fame Let M [ M ; m ] MW [ M ; m ] M ( M m ) n ( / λ ) M m n / λ [ I mn + mn ; ( / λ )m + ( / λ ) m] I; [ ] We ae left wth 4 degee of feedom (uto cale): (n, λ ) U. of Mlano, Lectue : multvew

12 [I;]P [ H ;e ]P [I;] Choce of Canoncal Fame I I / λ λn P λ n I λn P λ x y P x y P µ µ U. of Mlano, Lectue : multvew

13 Choce of Canoncal Fame [ H ;e ] [H ;e ] µ [H ;e ] n I / λ µ n I H + e n ; ( / λ )e / λ [ ] [ λ H + e n ; e ] whee n, ) ( λ [ ] µ λh + e n ; e ae fee vaable U. of Mlano, Lectue : multvew 3

14 Famly of Homogahy Matce [ λh + e n ; e ]P H π λh + e n H π Stand fo the famly of D oectve tanfomaton between two fxed mage nduced by a lane n ace U. of Mlano, Lectue : multvew 4

15 Famly of Homogahy Matce H π H + d e n when d H π H K RK n d ft camea fame K RK the homogahy matx nduced by the lane at nfnty U. of Mlano, Lectue : multvew 5

16 Recontucton Poblem H ; e [ ] µ H + µ e We wh to olve fo the moton and tuctue fom matche Wthout addtonal nfomaton we cannot olve unquely fo H becaue H detemned u to a 4-aamete famly (oton of a efeence lane n ace). U. of Mlano, Lectue : multvew 6

17 A me on oectve geomety of the lane U. of Mlano, Lectue : multvew 7

18 ax + by + c Poectve Geomety of the Plane Equaton of a lne n the D lane he lne eeented by the vecto and l l ( a, b, c ) ( x, y,) Coeondence between lne and vecto ae not - becaue λa, λb, c ) eeent the ame lne ( λl ), λ ( λ he vecto (,,) doe not eeent any lne. wo vecto dffeng by a cale facto ae equvalent. h equvalence cla called homogenou vecto. Any vecto ( a, b, c ) a eeentaton of the equvalence cla. U. of Mlano, Lectue : multvew 8

19 Poectve Geomety of the Plane A ont ( x, y le on the lne (concdent wth) whch eeented by ff l l ( a, b, c ) But alo ( λ ) l ) ( λx, λy, λ ), λ ( 3 x, x, x ) eeent the ont he vecto eeent the ont ( x x 3, x x 3 ) ( x, y (,,) doe not eeent any ont. ) Pont and lne ae dual to each othe (only n the D cae!). U. of Mlano, Lectue : multvew 9

20 Poectve Geomety of the Plane ( ) ( ) note: ( a b ) c det( a, b, c ) Lewe, l U. of Mlano, Lectue : multvew q q l

21 U. of Mlano, Lectue : multvew Lne and Pont at Infnty Conde lne c b a ),, ( c b a ),, ( ) ( a b a b c c ac ac cb bc whch eeent the ont ), ( a b wth nfntely lage coodnate λ b a All meet at the ame ont a b ont at nfnty

22 Lne and Pont at Infnty he ont ( x x, x,), x, ( x, x,) le on a lne he lne he ont A lne l (,,) ( x x, x,), x, ( a, b, λ ) meet (whch the decton of the lne) called the lne at nfnty l (,,) ae called deal ont. a at b λ b a U. of Mlano, Lectue : multvew

23 A Model of the Poectve Plane ( x, x,) deal ont x l (,,) the lane x x x 3 x ( 3 λx, λx, λx ), λ Pont ae eeented a lne (ay) though the ogn Lne ae eeented a lane though the ogn U. of Mlano, Lectue : multvew 3

24 A Model of the Poectve Plane P n {[ x,..., x n ] [,..., ] : [ x,..., x n ] [λx,..., λx n ], λ } {lne though the ogn n n + R } {-dm ubace of n + R } U. of Mlano, Lectue : multvew 4

25 Poectve anfomaton n P he tudy of oete of the oectve lane that ae nvaant unde a gou of tanfomaton. Poectvty: h : P P that ma lne to lne (.e. eeve colneaty) Any nvetble 3x3 matx a Poectvty: Let,, 3 Colnea ont,.e. l l H H the ont H le on the lne H l heefoe H eeve colneaty. H called homogahy, colneaton H A homogahy detemned by 8 aamete. the dual. U. of Mlano, Lectue : multvew 5

26 Poectve anfomaton n P eectvty (6 d.o.f) A comoton of eectvte fom a lane π to othe lane and bac to π a oectvty. Evey oectvty can be eeented n th way. U. of Mlano, Lectue : multvew 6

27 Poectve anfomaton n P Examle, a eectvty n D: Lne adonng matchng ont ae concuent c a b a b c Lne adonng matchng ont (a,a ),(b,b ),(c,c ) ae not concuent U. of Mlano, Lectue : multvew 7

28 Poectve anfomaton n P l (,,) not nvaant unde H: Pont on l ae ( x, x,) H x x x xh + x h x x 3 x 3 not necealy Paallel lne do not eman aallel! l maed to H l U. of Mlano, Lectue : multvew 8

29 Poectve Ba A Smlex n R n + a et of n+ ont uch that no ubet Of n+ of them le on a hyelane (lnealy deendent). In P a Smlex 4 ont heoem: thee a unque colneaton between any two Smlexe U. of Mlano, Lectue : multvew 9

30 Poectve Invaant Invaant ae meauement that eman fxed unde colneaton # of ndeendent nvaant # d.o.f of confguaton - # d.o.f of tan. Ex: D cae H x H ha 3 d.o.f A ont n D eeented by aamete. 4 ont we have: 4-3 nvaant (co ato) D cae: H ha 8 d.o.f, a ont ha d.o.f thu 5 ont nduce nvaant U. of Mlano, Lectue : multvew 3

31 Poectve Invaant he co-ato of 4 ont: α ab ac cd bd a b b d 4 emutaton of the 4 ont fomng 6 gou: α,, α α α α,,, α α α U. of Mlano, Lectue : multvew 3

32 5 ont gve u d.o.f, thu -8 nvaant whch eeent D x y, z, u Poectve Invaant, ae the 4 ba ont (mlex) y α < z, u, x x x, β < z, u, y y y, > > y u y u z u x y, ae detemned unquely by α, β x y x Pont of nteecton eeved unde oectvty (exece) x, y unquely detemned U. of Mlano, Lectue : multvew 3

33 Eola Geomety and Fundamental Matx U. of Mlano, Lectue : multvew 33

34 Remnde: [ I ;] P [ H ; e ] P x y P µ [ λh + e n ; e ]P P µ H µ e π + H π λh + e n H π Stand fo the famly of D oectve tanfomaton between two fxed mage nduced by a lane n ace U. of Mlano, Lectue : multvew 34

35 H µ e π + Plane + Paallax P ( x, y,, µ ) [ I,] P π [ H π e ]P π H π e what doe µ tand fo? what would we obtan afte elmnatng µ U. of Mlano, Lectue : multvew 35

36 Plane + Paallax H π + µ e We have ued 4 ace ont fo a ba: 3 fo the efeence lane fo the efeence ont (calng) Snce 4 ont detemne an affne ba: d P d P Z µ Z Z d d µ called elatve affne tuctue Z Note: we need 5 ont fo a oectve ba. he 5 th ont the ft camea cente. U. of Mlano, Lectue : multvew 36

37 Note: A oectve nvaant H µ e π + H ˆ ˆ µ e µ ˆ µ π + dˆ dˆ d d d dˆ P d Z dˆ P Z µ Z Z d d h nvaant ( oectve deth ) ndeendent of both camea oton, theefoe oectve. 5 ba ont: 4 non-colana defne two lane, and A 5 th ont fo calng. U. of Mlano, Lectue : multvew 37

38 H µ e π + Fundamental Matx P ( x, y,, µ ) π H π e an [ H e ] π ( e H ) π ([ e] Hπ ) F U. of Mlano, Lectue : multvew 38

39 Fundamental Matx ([ e] H ) π F Defne a blnea matchng contant whoe coeffcent deend only on the camea geomety (hae wa elmnated) F doe not deend on the choce of the efeence lane [ e] λ [ e] H Hπ [ e] ( H + e n ) U. of Mlano, Lectue : multvew 39

40 Eole fom F Note: any homogahy matx ma between eole: c e H π e e e c U. of Mlano, Lectue : multvew 4

41 Eole fom F Fe [ e] H e [ e] e F e [ e] e H F the eola lne of - the oecton of the lne of ght onto the econd mage. U. of Mlano, Lectue : multvew 4

42 Etmatng F fom matchng ont F,..., 8 Lnea oluton F,..., 7 det( F) N on-lnea oluton det( F) cubc n the element of F, thu we hould exect 3 oluton. U. of Mlano, Lectue : multvew 4

43 U. of Mlano, Lectue : multvew 43 Etmatng F fom Homogahe F H π ew-ymmetc (.e. ovde 6 contant on F) + H e H H e n e H F H ] [ ] [ ) ( λ λ π + H e H n e H e H H F ] [ ) ( ] [ λ λ π π H π F F H homogahy matce ae equed fo a oluton fo F

44 F Induce a Homogahy π F δ ] F [δ a homogahy matx nduced by the lane defned by the on of the mage lne δ and the camea cente U. of Mlano, Lectue : multvew 44

45 Poectve Recontucton. Solve fo F va the ytem F (8 ont o 7 ont). Solve fo e va the ytem F e 3. Select an abtay vecto δ δ e 4. [ I ] and [ δ ] e ] F ae a a of camea matce. [ δ ] F + µ e U. of Mlano, Lectue : multvew 45

46 Why 3 vew? U. of Mlano, Lectue : multvew 46

47 focal Geomety he thee fundamental matce comletely decbe the tfocal geomety (a long a the thee camea cente ae not collnea) F e3 e e3 e 3 F e3 e e Lewe: e F e 3 3 e 3 e 3 e 3 F3 e e 3 e 3 Each contant non-lnea n the ente of the fundamental matce (becaue the eole ae the eectve null ace) U. of Mlano, Lectue : multvew 47 3

48 focal Geomety e 3 F e3 e 3 F3e e 3 F3 e 3 fundamental matce ovde aamete. Subtact 3 contant, hu we have that the tfocal geomety detemned by 8 aamete. h content wth the taght-fowad countng: 3x 5 8 (3 camea matce ovde 33 aamete, mnu the oectve ba) U. of Mlano, Lectue : multvew 48

49 What Goe Wong wth 3 vew? e3 e e e 3 e3 e 3 contant each, thu we have -65 aamete e 3 e 3 3 e e 3 e e 3 U. of Mlano, Lectue : multvew 49

50 What Goe Wong wth 3 vew? e 3 e 3 3 e e 3 e e 3 t α 3 t + t hu, to eeent t3 we need only aamete (ntead of 3). t t t3 8-6 aamete ae needed to eeent the tfocal geomety n th cae. but the awe fundamental matce can account fo only 5! U. of Mlano, Lectue : multvew 5

51 What Ele Goe Wong: Reoecton F F3 3 Gven, and the awe F-mat one can dectly detemne the oton of the matchng ont h fal when the 3 camea cente ae collnea becaue all thee lne of ght ae colana thu thee only one eola lne! F 3 3 F 3 U. of Mlano, Lectue : multvew 5

52 focal Contant U. of Mlano, Lectue : multvew 5

53 he focal Contant I [ ]P A e [ ]P B e [ ]P x y x y U. of Mlano, Lectue : multvew 53

54 he focal Contant [ A e ]P A e [ ]P A e [ ]P [ B e ]P I [ ]P B e [ ]P B e [ ]P ( x ) P ( y ) P U. of Mlano, Lectue : multvew 54

55 U. of Mlano, Lectue : multvew P e B e B e A e A y x Evey 4x4 mno mut vanh! of thoe nvolve all 3 vew, they ae aanged n 3 gou Deendng on whch vew the efeence vew. he focal Contant

56 U. of Mlano, Lectue : multvew 56 e B e B e A e A y x he efeence vew Chooe ow fom hee Chooe ow fom hee We hould exect to have 4 matchng contant ),, ( f he focal Contant

57 Exandng the detemnant: he focal Contant A + µ e A + e µ, B + µ e B + e µ, elmnate µ A B e e ( e )( A ) ( e )( B,, ) U. of Mlano, Lectue : multvew 57

58 he focal Contant [ A e ] P What gong on geometcally: ( A, e) a lane C y C P x 4 lane nteect at P! U. of Mlano, Lectue : multvew 58 C

59 Pme on Covaant-Contavaant conventon U. of Mlano, Lectue : multvew 59

60 Index Notaton Goal: eeent the oeaton of nne-oduct and oute-oduct A vecto ha ue-ct unnng ndex when t eeent a ont A vecto ha ubct unnng ndex when t eeent a hyelane Examle: (,, 3 ) Reeent a ont n the oectve lane (,, ) 3 Reeent a lne n the oectve lane U. of Mlano, Lectue : multvew 6

61 An oute-oduct: uv an obect (-valence teno) whoe ente ae u v,..., u,..., uvm,..., unv n v m Note: th the oute-oduct of two vecto: uv uv.. unv uv. u n. v m m n m (an- matx) a c c + d d x x A geneal -valence teno a um of an- -valence teno U. of Mlano, Lectue : multvew 6

62 Lewe, u v u v u v Ae oute-oduct contng of the ame element, but a a mang cay each a dffeent meanng (decbed late). hee ae alo called mxed teno, whee the ue-ct called conta-vaant ndex and the ubct called covaant ndex. U. of Mlano, Lectue : multvew 6

63 he nne-oduct (contacton): Summaton ule: ame ndex n contavaant and covaant oton ae ummed ove. h ometme called the Enten ummaton conventon. u v u v + u v u n v n U. of Mlano, Lectue : multvew 63

64 he nne-oduct (contacton): a u a u + a u a u n n v Note: th the famla matx-vecto multlcaton: Au whee the ue-ct un ove the ow of the matx v Note: the -valence teno a ma ont to ont U. of Mlano, Lectue : multvew 64

65 Lewe, a u v Ma hyelane (lne n D) to hyelane Note: th equvalent to A u We have een n the at that f hen H l l v H ma lne fom vew to vew a homogahy,, Let 3 Colnea ont,.e. l l H H the ont H le on the lne H l Wth the ndex notaton we get th oety mmedately! U. of Mlano, Lectue : multvew 65

66 he comlete lt: a u v Ma ont to ont a u v Ma hyelane (lne n D) to hyelane a u v Ma ont to hyelane a u v Ma hyelane to ont U. of Mlano, Lectue : multvew 66

67 Moe Examle: un ove the ow a b c h the matx oduct AB C u v un ove the column H u H H Mut be a ont ae a ont n ft fame, a hyelane n the econd fame and oduce a ont n the thd fame Mut be a matx (-valence teno) f u(,, ) then th a lce of the teno. H U. of Mlano, Lectue : multvew 67

68 H 5 H U. of Mlano, Lectue : multvew 68

69 U. of Mlano, Lectue : multvew det det det q q q q q q q q ε q q ε q he Co-oduct eno

70 U. of Mlano, Lectue : multvew 7 v u v u ] [ ] [ 3 3 u u u u u u u ε u he co-oduct teno defned uch that Poduce the matx ] [u.e., the ente ae,-,

71 U. of Mlano, Lectue : multvew 7 ] [ 3 3 u u u u u u u ε ε 3 ε + + ] [ 3 3 u u u u u ε ε ε ε

72 he focal eno U. of Mlano, Lectue : multvew 7

73 he focal eno ( e )( A ) ( e )( B ) New ndex notaton: -mage, -mage, -mage 3 A + µ e a + µ e a ont n mage a lne n mage e a ont n mage U. of Mlano, Lectue : multvew 73

74 l he focal eno l, ae the two lne concdent wth,.e. l m m m, ae the two lne concdent wth,.e. l a + µ l e m b + µ m e Elmnate µ l m m l ( e )( b ) ( e )( a ) U. of Mlano, Lectue : multvew 74

75 U. of Mlano, Lectue : multvew 75 he focal eno ) )( ( ) )( ( l m m l a e b e Reaange tem: ) ( m l a e b e he tfocal teno : a e b e,, m l

76 he focal eno l m l x y m x y he fou tlneate : x 3 - x x 33 + x 3 - y 3 - y x 33 + x 3 - x 3 - x y 33 + y 3 - y 3 - y y 33 + x 3 - U. of Mlano, Lectue : multvew 76

77 U. of Mlano, Lectue : multvew 77 he focal eno β α + δ γ + ) )( ( + + δ γ β α A tlneaty a contacton wth a ont-lne-lne whee the lne ae concdent wth the eectve matchng ont.

78 Slce of the focal eno Now that we have an exlct fom of the teno, what can we do wth t?? he eult mut be a contavaant vecto (a ont). h ont concdent wth fo all lne concdent wth e he ont eoecton equaton (wll wo when camea cente ae collnea a well). Note: eoecton oble afte obevng 7 matchng ont, (becaue one need 7 matchng tlet to olve fo the teno). h n contat to eoecton ung awe fundamental matce Whch eque 8 matchng ont (n ode to olve fo the F-mat). U. of Mlano, Lectue : multvew 78

79 Slce of the focal eno 3 U. of Mlano, Lectue : multvew 79

80 Slce of the focal eno? he eult mut be a lne. q Lne eoecton equaton O 3 matchng lne ae neceay fo O q olvng fo the teno (comaed to 7 matchng ont) O U. of Mlano, Lectue : multvew 8

81 Slce of the focal eno δ? he eult mut be a matx. H δ δ the eoecton equaton δ H a homogahy matx 3 H δ δ a famly of homogahy matce (fom to ) nduced by the famly of lane concdant wth the 3 d camea cente. U. of Mlano, Lectue : multvew 8

82 Slce of the focal eno δ the homogahy matx fom to 3 nduced by the lane defned by the mage lne δ and the econd camea cente. δ? δ he eult a ont on the eola lne of δ on mage 3 the eoecton equaton 3 F 3 δ U. of Mlano, Lectue : multvew 8 δ

83 Slce of the focal eno δ G G I a ont on the eola lne δ F 3 an( G) (becaue t ma the dual lane onto collnea ont) F 3 δ null(g) F δ 3 null(g ) F 3 δ δ U. of Mlano, Lectue : multvew 83

84 U. of Mlano, Lectue : multvew 84 8 Paamete fo the focal eno a e b e ) ( ) ( e n a e e n b e + + e e n e e n + Ha 4 aamete ( ) mnu fo global cale mnu fo calng e,e to be unt vecto mnu 3 fo ettng n uch that B ha a vanhng column n 8 ndeendent aamete We hould exect to fnd 9 non-lnea contant among the 7 ente of the teno (admblty contant).

85 8 Paamete fo the focal eno What haen when the 3 camea cente ae collnea? (we aw that awe F-mat account fo 5 aamete). A e B e 3 e e B e A e h ovde two addtonal (non-lnea) contant, thu 8-6. U. of Mlano, Lectue : multvew 85

86 Item not Coveed Degeneate confguaton (Lnea Lne Comlex, Quatc Cuve) he ouce of the 9 admblty contant (come fom the homogahy lce). Concatenaton of tfocal teno along a equence U. of Mlano, Lectue : multvew 86

87 Quadfocal eno U. of Mlano, Lectue : multvew 87

88 Lnea Lne Comlex P L S l l H π Whee π any lane concdent wth L ( l ) [ l ] x H [ l] G π x Fo all lne ang though and all lne ang though U. of Mlano, Lectue : multvew 88 π

89 G π unque l π L π v l H π λhπ + v l Gπ λ G ( Hπ + v l )[ l] x Hπ[ l] x π U. of Mlano, Lectue : multvew 89

90 L P t [ I ] P [ A v ] P [ B v ] P [ C v ] P U. of Mlano, Lectue : multvew 9

91 L P t [ C v] t q [ B v] We wh to contuct an LLC mang Q(,t) whoe enel L Q(, t) q q t l Q Fo all lne ang though and all lne q ang though U. of Mlano, Lectue : multvew 9 l

92 U. of Mlano, Lectue : multvew 9 P L t [ v] B [ v] C t ] [I λ λ + t v t C v B β α λ t C v B t v ) ( ) ( λ

93 [ I ] P [ A v ] P [ B v ] P [ C v ] P λ n L P σ π t A B A σ A + v n Q (, t) A [ λ] A[ λ] + v( n λ) σ ( n λ) B U. of Mlano, Lectue : multvew 93 C t

94 U. of Mlano, Lectue : multvew 94 + ] [ ) ( ] [ ) ( ) ( ), ( B A t v t A C v t C B v t Q n v A A t Q ) ( ] [ ] [ ), ( λ λ λ σ + t C B n ) ( λ t C v B t v ) ( ) ( λ ] [ ) ( ] [ ) ( ) )( ( + q B A t v q t A C v q t C B v ), ( q t Q

95 U. of Mlano, Lectue : multvew 95 P L q π B A B LLC between vew, wth enel L : [ ] B A ] [ q B A Fo all q,, though,, ] [ ) ( ] [ ) ( ) )( ( + q B A t v q t A C v q t C B v

96 U. of Mlano, Lectue : multvew 96 ] [ ) ( ] [ ) ( ) )( ( + q B A t v q t A C v q t C B v P q π B A B ] [ q B A Fo all q,, though,, A ) ( A B q [ ] B A q an

97 U. of Mlano, Lectue : multvew 97 P q π A B Dual Homogahy eno ) ( A B q ) ( n u un b a q ε H q

98 U. of Mlano, Lectue : multvew 98 ] [ ) ( ] [ ) ( ) )( ( + q B A t v q t A C v q t C B v ) ( ) ( ) ( + l l l l l l q H v t t q H v t q H v l l Q t q l l l l H v H v H v Q + Quadfocal eno a v b v he tlnea (tfocal) teno

99 Gauge Invaance [ I ], [ A + vw v ], [ B + vw v ], [ C + vw v ] q t l Q l l l Q Q Fo all choce of w U. of Mlano, Lectue : multvew 99

100 How Many matchng ont ae needed? q η µ ν t σ Q l η, µ, ν, σ, l t ont: 6 quadlnea equaton fo Q nd ont: 5 equaton 3 d ont: 4 equaton U. of Mlano, Lectue : multvew

101 Sngle Contacton δ l lq H P π δ U. of Mlano, Lectue : multvew

102 Double Contacton δ l µ l Q E LLC between vew, δ µ le Contacton t l Q l U. of Mlano, Lectue : multvew

103 Item not Coveed Quad contucted fom focal and Fundamental Matx Fundamental Matx fom Quadfocal focal fom Quadfocal Poecton Matce fom Quadfocal 5 Non-lnea Contant U. of Mlano, Lectue : multvew 3

Multi-linear Systems and Invariant Theory. in the Context of Computer Vision and Graphics. Class 4: Mutli-View 3D-from-2D. CS329 Stanford University

Multi-linear Systems and Invariant Theory. in the Context of Computer Vision and Graphics. Class 4: Mutli-View 3D-from-2D. CS329 Stanford University Mult-lna Sytm and Invaant hoy n th Contxt of Comut Von and Gahc Cla 4: Mutl-Vw 3D-fom-D CS39 Stanfod Unvty Amnon Shahua Cla 4 Matal W Wll Cov oday Eola Gomty and Fundamntal Matx h lan+aallax modl and latv

More information

[ ] OP = OO' + Ut + Vn + Wb. The Structure of a Projection Matrix. R = t n b. The Structure of a Projection Matrix

[ ] OP = OO' + Ut + Vn + Wb. The Structure of a Projection Matrix. R = t n b. The Structure of a Projection Matrix Ml-lnea Syem fo 3D-fom-D Ineeaon Lece Ml-ew Geomey fom a Saonay Scene mnon Shaha Hebew Uney of Jealem Iael U. of Mlano, 5.7.4 Lece : mlew Maeal We Wll Coe oday he ce of 3D->D oecon max me on oece geomey

More information

Engineering Mechanics. Force resultants, Torques, Scalar Products, Equivalent Force systems

Engineering Mechanics. Force resultants, Torques, Scalar Products, Equivalent Force systems Engneeng echancs oce esultants, Toques, Scala oducts, Equvalent oce sstems Tata cgaw-hll Companes, 008 Resultant of Two oces foce: acton of one bod on anothe; chaacteed b ts pont of applcaton, magntude,

More information

Rigid Bodies: Equivalent Systems of Forces

Rigid Bodies: Equivalent Systems of Forces Engneeng Statcs, ENGR 2301 Chapte 3 Rgd Bodes: Equvalent Sstems of oces Intoducton Teatment of a bod as a sngle patcle s not alwas possble. In geneal, the se of the bod and the specfc ponts of applcaton

More information

Set of square-integrable function 2 L : function space F

Set of square-integrable function 2 L : function space F Set of squae-ntegable functon L : functon space F Motvaton: In ou pevous dscussons we have seen that fo fee patcles wave equatons (Helmholt o Schödnge) can be expessed n tems of egenvalue equatons. H E,

More information

Detection and Estimation Theory

Detection and Estimation Theory ESE 54 Detecton and Etmaton Theoy Joeph A. O Sullvan Samuel C. Sach Pofeo Electonc Sytem and Sgnal Reeach Laboatoy Electcal and Sytem Engneeng Wahngton Unvety 411 Jolley Hall 314-935-4173 (Lnda anwe) jao@wutl.edu

More information

Exam 1. Sept. 22, 8:00-9:30 PM EE 129. Material: Chapters 1-8 Labs 1-3

Exam 1. Sept. 22, 8:00-9:30 PM EE 129. Material: Chapters 1-8 Labs 1-3 Eam ept., 8:00-9:30 PM EE 9 Mateal: Chapte -8 Lab -3 tandadzaton and Calbaton: Ttaton: ue of tandadzed oluton to detemne the concentaton of an unknown. Rele on a eacton of known tochomet, a oluton wth

More information

Chapter I Matrices, Vectors, & Vector Calculus 1-1, 1-9, 1-10, 1-11, 1-17, 1-18, 1-25, 1-27, 1-36, 1-37, 1-41.

Chapter I Matrices, Vectors, & Vector Calculus 1-1, 1-9, 1-10, 1-11, 1-17, 1-18, 1-25, 1-27, 1-36, 1-37, 1-41. Chapte I Matces, Vectos, & Vecto Calculus -, -9, -0, -, -7, -8, -5, -7, -36, -37, -4. . Concept of a Scala Consde the aa of patcles shown n the fgue. he mass of the patcle at (,) can be epessed as. M (,

More information

Ch. 3: Forward and Inverse Kinematics

Ch. 3: Forward and Inverse Kinematics Ch. : Fowa an Invee Knemat Reap: The Denavt-Hatenbeg (DH) Conventon Repeentng eah nvual homogeneou tanfomaton a the pout of fou ba tanfomaton: pout of fou ba tanfomaton: x a x z z a a a Rot Tan Tan Rot

More information

Test 1 phy What mass of a material with density ρ is required to make a hollow spherical shell having inner radius r i and outer radius r o?

Test 1 phy What mass of a material with density ρ is required to make a hollow spherical shell having inner radius r i and outer radius r o? Test 1 phy 0 1. a) What s the pupose of measuement? b) Wte all fou condtons, whch must be satsfed by a scala poduct. (Use dffeent symbols to dstngush opeatons on ectos fom opeatons on numbes.) c) What

More information

Scalars and Vectors Scalar

Scalars and Vectors Scalar Scalas and ectos Scala A phscal quantt that s completel chaacteed b a eal numbe (o b ts numecal value) s called a scala. In othe wods a scala possesses onl a magntude. Mass denst volume tempeatue tme eneg

More information

1. A body will remain in a state of rest, or of uniform motion in a straight line unless it

1. A body will remain in a state of rest, or of uniform motion in a straight line unless it Pncples of Dnamcs: Newton's Laws of moton. : Foce Analss 1. A bod wll eman n a state of est, o of unfom moton n a staght lne unless t s acted b etenal foces to change ts state.. The ate of change of momentum

More information

E-Companion: Mathematical Proofs

E-Companion: Mathematical Proofs E-omnon: Mthemtcl Poo Poo o emm : Pt DS Sytem y denton o t ey to vey tht t ncee n wth d ncee n We dene } ] : [ { M whee / We let the ttegy et o ech etle n DS e ]} [ ] [ : { M w whee M lge otve nume oth

More information

Lecture 9-3/8/10-14 Spatial Description and Transformation

Lecture 9-3/8/10-14 Spatial Description and Transformation Letue 9-8- tl Deton nd nfomton Homewo No. Due 9. Fme ngement onl. Do not lulte...8..7.8 Otonl et edt hot oof tht = - Homewo No. egned due 9 tud eton.-.. olve oblem:.....7.8. ee lde 6 7. e Mtlb on. f oble.

More information

Inference for A One Way Factorial Experiment. By Ed Stanek and Elaine Puleo

Inference for A One Way Factorial Experiment. By Ed Stanek and Elaine Puleo Infeence fo A One Way Factoial Expeiment By Ed Stanek and Elaine Puleo. Intoduction We develop etimating equation fo Facto Level mean in a completely andomized one way factoial expeiment. Thi development

More information

Physics 11b Lecture #2. Electric Field Electric Flux Gauss s Law

Physics 11b Lecture #2. Electric Field Electric Flux Gauss s Law Physcs 11b Lectue # Electc Feld Electc Flux Gauss s Law What We Dd Last Tme Electc chage = How object esponds to electc foce Comes n postve and negatve flavos Conseved Electc foce Coulomb s Law F Same

More information

Solving the Dirac Equation: Using Fourier Transform

Solving the Dirac Equation: Using Fourier Transform McNa Schola Reeach Jounal Volume Atcle Solvng the ac quaton: Ung oue Tanfom Vncent P. Bell mby-rddle Aeonautcal Unvety, Vncent.Bell@my.eau.edu ollow th and addtonal wok at: http://common.eau.edu/na Recommended

More information

Chapter Fifiteen. Surfaces Revisited

Chapter Fifiteen. Surfaces Revisited Chapte Ffteen ufaces Revsted 15.1 Vecto Descpton of ufaces We look now at the vey specal case of functons : D R 3, whee D R s a nce subset of the plane. We suppose s a nce functon. As the pont ( s, t)

More information

EE 5337 Computational Electromagnetics (CEM)

EE 5337 Computational Electromagnetics (CEM) 7//28 Instucto D. Raymond Rumpf (95) 747 6958 cumpf@utep.edu EE 5337 Computatonal Electomagnetcs (CEM) Lectue #6 TMM Extas Lectue 6These notes may contan copyghted mateal obtaned unde fa use ules. Dstbuton

More information

Part V: Velocity and Acceleration Analysis of Mechanisms

Part V: Velocity and Acceleration Analysis of Mechanisms Pat V: Velocty an Acceleaton Analyss of Mechansms Ths secton wll evew the most common an cuently pactce methos fo completng the knematcs analyss of mechansms; escbng moton though velocty an acceleaton.

More information

The Backpropagation Algorithm

The Backpropagation Algorithm The Backpopagaton Algothm Achtectue of Feedfowad Netwok Sgmodal Thehold Functon Contuctng an Obectve Functon Tanng a one-laye netwok by teepet decent Tanng a two-laye netwok by teepet decent Copyght Robet

More information

Chapter 8. Linear Momentum, Impulse, and Collisions

Chapter 8. Linear Momentum, Impulse, and Collisions Chapte 8 Lnea oentu, Ipulse, and Collsons 8. Lnea oentu and Ipulse The lnea oentu p of a patcle of ass ovng wth velocty v s defned as: p " v ote that p s a vecto that ponts n the sae decton as the velocty

More information

V V The circumflex (^) tells us this is a unit vector

V V The circumflex (^) tells us this is a unit vector Vecto Vecto have Diection and Magnitude Mike ailey mjb@c.oegontate.edu Magnitude: V V V V x y z vecto.pptx Vecto Can lo e Defined a the oitional Diffeence etween Two oint 3 Unit Vecto have a Magnitude

More information

24-2: Electric Potential Energy. 24-1: What is physics

24-2: Electric Potential Energy. 24-1: What is physics D. Iyad SAADEDDIN Chapte 4: Electc Potental Electc potental Enegy and Electc potental Calculatng the E-potental fom E-feld fo dffeent chage dstbutons Calculatng the E-feld fom E-potental Potental of a

More information

Basic propositional and. The fundamentals of deduction

Basic propositional and. The fundamentals of deduction Baic ooitional and edicate logic The fundamental of deduction 1 Logic and it alication Logic i the tudy of the atten of deduction Logic lay two main ole in comutation: Modeling : logical entence ae the

More information

PHY126 Summer Session I, 2008

PHY126 Summer Session I, 2008 PHY6 Summe Sesson I, 8 Most of nfomaton s avalable at: http://nngoup.phscs.sunsb.edu/~chak/phy6-8 ncludng the sllabus and lectue sldes. Read sllabus and watch fo mpotant announcements. Homewok assgnment

More information

Chapter 19 Webassign Help Problems

Chapter 19 Webassign Help Problems Chapte 9 Webaign Help Poblem 4 5 6 7 8 9 0 Poblem 4: The pictue fo thi poblem i a bit mileading. They eally jut give you the pictue fo Pat b. So let fix that. Hee i the pictue fo Pat (a): Pat (a) imply

More information

Capítulo. Three Dimensions

Capítulo. Three Dimensions Capítulo Knematcs of Rgd Bodes n Thee Dmensons Mecánca Contents ntoducton Rgd Bod Angula Momentum n Thee Dmensons Pncple of mpulse and Momentum Knetc Eneg Sample Poblem 8. Sample Poblem 8. Moton of a Rgd

More information

If there are k binding constraints at x then re-label these constraints so that they are the first k constraints.

If there are k binding constraints at x then re-label these constraints so that they are the first k constraints. Mathematcal Foundatons -1- Constaned Optmzaton Constaned Optmzaton Ma{ f ( ) X} whee X {, h ( ), 1,, m} Necessay condtons fo to be a soluton to ths mamzaton poblem Mathematcally, f ag Ma{ f ( ) X}, then

More information

Rotational Kinematics. Rigid Object about a Fixed Axis Western HS AP Physics 1

Rotational Kinematics. Rigid Object about a Fixed Axis Western HS AP Physics 1 Rotatonal Knematcs Rgd Object about a Fxed Axs Westen HS AP Physcs 1 Leanng Objectes What we know Unfom Ccula Moton q s Centpetal Acceleaton : Centpetal Foce: Non-unfom a F c c m F F F t m ma t What we

More information

Computational Vision. Camera Calibration

Computational Vision. Camera Calibration Comutatonal Vson Camea Calbaton uo hate 6 Camea Calbaton Poblem: Estmate amea s etns & ntns aametes MthdU Method: Use mage(s) () o knon sene ools: Geomet amea models SVD and onstaned least-squaes Lne etaton

More information

19 The Born-Oppenheimer Approximation

19 The Born-Oppenheimer Approximation 9 The Bon-Oppenheme Appoxmaton The full nonelatvstc Hamltonan fo a molecule s gven by (n a.u.) Ĥ = A M A A A, Z A + A + >j j (883) Lets ewte the Hamltonan to emphasze the goal as Ĥ = + A A A, >j j M A

More information

Variable Structure Control ~ Basics

Variable Structure Control ~ Basics Varable Structure Control ~ Bac Harry G. Kwatny Department of Mechancal Engneerng & Mechanc Drexel Unverty Outlne A prelmnary example VS ytem, ldng mode, reachng Bac of dcontnuou ytem Example: underea

More information

ˆ x ESTIMATOR. state vector estimate

ˆ x ESTIMATOR. state vector estimate hapte 9 ontolle Degn wo Independent Step: Feedback Degn ontol Law =- ame all tate ae acceble a lot of eno ae necea Degn of Etmato alo called an Obeve whch etmate the ente tate vecto gven the otpt and npt

More information

(8) Gain Stage and Simple Output Stage

(8) Gain Stage and Simple Output Stage EEEB23 Electoncs Analyss & Desgn (8) Gan Stage and Smple Output Stage Leanng Outcome Able to: Analyze an example of a gan stage and output stage of a multstage amplfe. efeence: Neamen, Chapte 11 8.0) ntoducton

More information

Energy in Closed Systems

Energy in Closed Systems Enegy n Closed Systems Anamta Palt palt.anamta@gmal.com Abstact The wtng ndcates a beakdown of the classcal laws. We consde consevaton of enegy wth a many body system n elaton to the nvese squae law and

More information

2/24/2014. The point mass. Impulse for a single collision The impulse of a force is a vector. The Center of Mass. System of particles

2/24/2014. The point mass. Impulse for a single collision The impulse of a force is a vector. The Center of Mass. System of particles /4/04 Chapte 7 Lnea oentu Lnea oentu of a Sngle Patcle Lnea oentu: p υ It s a easue of the patcle s oton It s a vecto, sla to the veloct p υ p υ p υ z z p It also depends on the ass of the object, sla

More information

Chapter 11. Supplemental Text Material. The method of steepest ascent can be derived as follows. Suppose that we have fit a firstorder

Chapter 11. Supplemental Text Material. The method of steepest ascent can be derived as follows. Suppose that we have fit a firstorder S-. The Method of Steepet cent Chapter. Supplemental Text Materal The method of teepet acent can be derved a follow. Suppoe that we have ft a frtorder model y = β + β x and we wh to ue th model to determne

More information

PHYS 705: Classical Mechanics. Derivation of Lagrange Equations from D Alembert s Principle

PHYS 705: Classical Mechanics. Derivation of Lagrange Equations from D Alembert s Principle 1 PHYS 705: Classcal Mechancs Devaton of Lagange Equatons fom D Alembet s Pncple 2 D Alembet s Pncple Followng a smla agument fo the vtual dsplacement to be consstent wth constants,.e, (no vtual wok fo

More information

Concept of Game Equilibrium. Game theory. Normal- Form Representation. Game definition. Lecture Notes II-1 Static Games of Complete Information

Concept of Game Equilibrium. Game theory. Normal- Form Representation. Game definition. Lecture Notes II-1 Static Games of Complete Information Game theoy he study of multeson decsons Fou tyes of games Statc games of comlete nfomaton ynamc games of comlete nfomaton Statc games of ncomlete nfomaton ynamc games of ncomlete nfomaton Statc v. dynamc

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 151 Lectue 18 Hamltonan Equatons of Moton (Chapte 8) What s Ahead We ae statng Hamltonan fomalsm Hamltonan equaton Today and 11/6 Canoncal tansfomaton 1/3, 1/5, 1/10 Close lnk to non-elatvstc

More information

Rotary motion

Rotary motion ectue 8 RTARY TN F THE RGD BDY Notes: ectue 8 - Rgd bod Rgd bod: j const numbe of degees of feedom 6 3 tanslatonal + 3 ota motons m j m j Constants educe numbe of degees of feedom non-fee object: 6-p

More information

Team. Outline. Statistics and Art: Sampling, Response Error, Mixed Models, Missing Data, and Inference

Team. Outline. Statistics and Art: Sampling, Response Error, Mixed Models, Missing Data, and Inference Team Stattc and Art: Samplng, Repone Error, Mxed Model, Mng Data, and nference Ed Stanek Unverty of Maachuett- Amhert, USA 9/5/8 9/5/8 Outlne. Example: Doe-repone Model n Toxcology. ow to Predct Realzed

More information

DYNAMICS VECTOR MECHANICS FOR ENGINEERS: Kinematics of Rigid Bodies in Three Dimensions. Seventh Edition CHAPTER

DYNAMICS VECTOR MECHANICS FOR ENGINEERS: Kinematics of Rigid Bodies in Three Dimensions. Seventh Edition CHAPTER Edton CAPTER 8 VECTOR MECANCS FOR ENGNEERS: DYNAMCS Fednand P. Bee E. Russell Johnston, J. Lectue Notes: J. Walt Ole Teas Tech Unvest Knematcs of Rgd Bodes n Thee Dmensons 003 The McGaw-ll Companes, nc.

More information

Integral Vector Operations and Related Theorems Applications in Mechanics and E&M

Integral Vector Operations and Related Theorems Applications in Mechanics and E&M Dola Bagayoko (0) Integal Vecto Opeatons and elated Theoems Applcatons n Mechancs and E&M Ι Basc Defnton Please efe to you calculus evewed below. Ι, ΙΙ, andιιι notes and textbooks fo detals on the concepts

More information

Machine Learning. Spectral Clustering. Lecture 23, April 14, Reading: Eric Xing 1

Machine Learning. Spectral Clustering. Lecture 23, April 14, Reading: Eric Xing 1 Machne Leanng -7/5 7/5-78, 78, Spng 8 Spectal Clusteng Ec Xng Lectue 3, pl 4, 8 Readng: Ec Xng Data Clusteng wo dffeent ctea Compactness, e.g., k-means, mxtue models Connectvty, e.g., spectal clusteng

More information

TRAVELING WAVES. Chapter Simple Wave Motion. Waves in which the disturbance is parallel to the direction of propagation are called the

TRAVELING WAVES. Chapter Simple Wave Motion. Waves in which the disturbance is parallel to the direction of propagation are called the Chapte 15 RAVELING WAVES 15.1 Simple Wave Motion Wave in which the ditubance i pependicula to the diection of popagation ae called the tanvee wave. Wave in which the ditubance i paallel to the diection

More information

A. Thicknesses and Densities

A. Thicknesses and Densities 10 Lab0 The Eath s Shells A. Thcknesses and Denstes Any theoy of the nteo of the Eath must be consstent wth the fact that ts aggegate densty s 5.5 g/cm (ecall we calculated ths densty last tme). In othe

More information

iclicker Quiz a) True b) False Theoretical physics: the eternal quest for a missing minus sign and/or a factor of two. Which will be an issue today?

iclicker Quiz a) True b) False Theoretical physics: the eternal quest for a missing minus sign and/or a factor of two. Which will be an issue today? Clce Quz I egsteed my quz tansmtte va the couse webste (not on the clce.com webste. I ealze that untl I do so, my quz scoes wll not be ecoded. a Tue b False Theoetcal hyscs: the etenal quest fo a mssng

More information

Summer Workshop on the Reaction Theory Exercise sheet 8. Classwork

Summer Workshop on the Reaction Theory Exercise sheet 8. Classwork Joned Physcs Analyss Cente Summe Wokshop on the Reacton Theoy Execse sheet 8 Vncent Matheu Contact: http://www.ndana.edu/~sst/ndex.html June June To be dscussed on Tuesday of Week-II. Classwok. Deve all

More information

CSJM University Class: B.Sc.-II Sub:Physics Paper-II Title: Electromagnetics Unit-1: Electrostatics Lecture: 1 to 4

CSJM University Class: B.Sc.-II Sub:Physics Paper-II Title: Electromagnetics Unit-1: Electrostatics Lecture: 1 to 4 CSJM Unvesty Class: B.Sc.-II Sub:Physcs Pape-II Ttle: Electomagnetcs Unt-: Electostatcs Lectue: to 4 Electostatcs: It deals the study of behavo of statc o statonay Chages. Electc Chage: It s popety by

More information

8 Baire Category Theorem and Uniform Boundedness

8 Baire Category Theorem and Uniform Boundedness 8 Bae Categoy Theoem and Unfom Boundedness Pncple 8.1 Bae s Categoy Theoem Valdty of many esults n analyss depends on the completeness popety. Ths popety addesses the nadequacy of the system of atonal

More information

Kinematics. Redundancy. Task Redundancy. Operational Coordinates. Generalized Coordinates. m task. Manipulator. Operational point

Kinematics. Redundancy. Task Redundancy. Operational Coordinates. Generalized Coordinates. m task. Manipulator. Operational point Mapulato smatc Jot Revolute Jot Kematcs Base Lks: movg lk fed lk Ed-Effecto Jots: Revolute ( DOF) smatc ( DOF) Geealzed Coodates Opeatoal Coodates O : Opeatoal pot 5 costats 6 paametes { postos oetatos

More information

Excellent web site with information on various methods and numerical codes for scattering by nonspherical particles:

Excellent web site with information on various methods and numerical codes for scattering by nonspherical particles: Lectue 5. Lght catteng and abopton by atmophec patcuate. at 3: Scatteng and abopton by nonpheca patce: Ray-tacng, T- Matx, and FDTD method. Objectve:. Type of nonpheca patce n the atmophee.. Ray-tacng

More information

FREE Download Study Package from website: &

FREE Download Study Package from website:  & .. Linea Combinations: (a) (b) (c) (d) Given a finite set of vectos a b c,,,... then the vecto xa + yb + zc +... is called a linea combination of a, b, c,... fo any x, y, z... R. We have the following

More information

gravity r2,1 r2 r1 by m 2,1

gravity r2,1 r2 r1 by m 2,1 Gavtaton Many of the foundatons of classcal echancs wee fst dscoveed when phlosophes (ealy scentsts and atheatcans) ted to explan the oton of planets and stas. Newton s ost faous fo unfyng the oton of

More information

SOME NEW SELF-DUAL [96, 48, 16] CODES WITH AN AUTOMORPHISM OF ORDER 15. KEYWORDS: automorphisms, construction, self-dual codes

SOME NEW SELF-DUAL [96, 48, 16] CODES WITH AN AUTOMORPHISM OF ORDER 15. KEYWORDS: automorphisms, construction, self-dual codes Факултет по математика и информатика, том ХVІ С, 014 SOME NEW SELF-DUAL [96, 48, 16] CODES WITH AN AUTOMORPHISM OF ORDER 15 NIKOLAY I. YANKOV ABSTRACT: A new method fo constuctng bnay self-dual codes wth

More information

V. Principles of Irreversible Thermodynamics. s = S - S 0 (7.3) s = = - g i, k. "Flux": = da i. "Force": = -Â g a ik k = X i. Â J i X i (7.

V. Principles of Irreversible Thermodynamics. s = S - S 0 (7.3) s = = - g i, k. Flux: = da i. Force: = -Â g a ik k = X i. Â J i X i (7. Themodynamcs and Knetcs of Solds 71 V. Pncples of Ievesble Themodynamcs 5. Onsage s Teatment s = S - S 0 = s( a 1, a 2,...) a n = A g - A n (7.6) Equlbum themodynamcs detemnes the paametes of an equlbum

More information

UNIT10 PLANE OF REGRESSION

UNIT10 PLANE OF REGRESSION UIT0 PLAE OF REGRESSIO Plane of Regesson Stuctue 0. Intoducton Ojectves 0. Yule s otaton 0. Plane of Regesson fo thee Vaales 0.4 Popetes of Resduals 0.5 Vaance of the Resduals 0.6 Summay 0.7 Solutons /

More information

Polar Coordinates. a) (2; 30 ) b) (5; 120 ) c) (6; 270 ) d) (9; 330 ) e) (4; 45 )

Polar Coordinates. a) (2; 30 ) b) (5; 120 ) c) (6; 270 ) d) (9; 330 ) e) (4; 45 ) Pola Coodinates We now intoduce anothe method of labelling oints in a lane. We stat by xing a oint in the lane. It is called the ole. A standad choice fo the ole is the oigin (0; 0) fo the Catezian coodinate

More information

CMSC 425: Lecture 5 More on Geometry and Geometric Programming

CMSC 425: Lecture 5 More on Geometry and Geometric Programming CMSC 425: Lectue 5 Moe on Geomety and Geometic Pogamming Moe Geometic Pogamming: In this lectue we continue the discussion of basic geometic ogamming fom the eious lectue. We will discuss coodinate systems

More information

Chapter 8 Sampling. Contents. Dr. Norrarat Wattanamongkhol. Lecturer. Department of Electrical Engineering, Engineering Faculty, sampling

Chapter 8 Sampling. Contents. Dr. Norrarat Wattanamongkhol. Lecturer. Department of Electrical Engineering, Engineering Faculty, sampling Content Chate 8 Samling Lectue D Noaat Wattanamongkhol Samling Theoem Samling of Continuou-Time Signal 3 Poceing Continuou-Time Signal 4 Samling of Dicete-Time Signal 5 Multi-ate Samling Deatment of Electical

More information

Image Enhancement: Histogram-based methods

Image Enhancement: Histogram-based methods Image Enhancement: Hitogam-baed method The hitogam of a digital image with gayvalue, i the dicete function,, L n n # ixel with value Total # ixel image The function eeent the faction of the total numbe

More information

Machine Learning 4771

Machine Learning 4771 Machne Leanng 4771 Instucto: Tony Jebaa Topc 6 Revew: Suppot Vecto Machnes Pmal & Dual Soluton Non-sepaable SVMs Kenels SVM Demo Revew: SVM Suppot vecto machnes ae (n the smplest case) lnea classfes that

More information

University of Pavia, Pavia, Italy. North Andover MA 01845, USA

University of Pavia, Pavia, Italy. North Andover MA 01845, USA Iteatoal Joual of Optmzato: heoy, Method ad Applcato 27-5565(Pt) 27-6839(Ole) wwwgph/otma 29 Global Ifomato Publhe (HK) Co, Ltd 29, Vol, No 2, 55-59 η -Peudoleaty ad Effcecy Gogo Gog, Noma G Rueda 2 *

More information

9/12/2013. Microelectronics Circuit Analysis and Design. Modes of Operation. Cross Section of Integrated Circuit npn Transistor

9/12/2013. Microelectronics Circuit Analysis and Design. Modes of Operation. Cross Section of Integrated Circuit npn Transistor Mcoelectoncs Ccut Analyss and Desgn Donald A. Neamen Chapte 5 The pola Juncton Tanssto In ths chapte, we wll: Dscuss the physcal stuctue and opeaton of the bpola juncton tanssto. Undestand the dc analyss

More information

Design of Recursive Digital Filters IIR

Design of Recursive Digital Filters IIR Degn of Recurve Dgtal Flter IIR The outut from a recurve dgtal flter deend on one or more revou outut value, a well a on nut t nvolve feedbac. A recurve flter ha an nfnte mule reone (IIR). The mulve reone

More information

Chapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters

Chapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters Chapter 6 The Effect of the GPS Sytematc Error on Deformaton Parameter 6.. General Beutler et al., (988) dd the frt comprehenve tudy on the GPS ytematc error. Baed on a geometrc approach and aumng a unform

More information

Then the number of elements of S of weight n is exactly the number of compositions of n into k parts.

Then the number of elements of S of weight n is exactly the number of compositions of n into k parts. Geneating Function In a geneal combinatoial poblem, we have a univee S of object, and we want to count the numbe of object with a cetain popety. Fo example, if S i the et of all gaph, we might want to

More information

Gravity. David Barwacz 7778 Thornapple Bayou SE, Grand Rapids, MI David Barwacz 12/03/2003

Gravity. David Barwacz 7778 Thornapple Bayou SE, Grand Rapids, MI David Barwacz 12/03/2003 avity David Bawacz 7778 Thonapple Bayou, and Rapid, MI 495 David Bawacz /3/3 http://membe.titon.net/daveb Uing the concept dicued in the peceding pape ( http://membe.titon.net/daveb ), I will now deive

More information

Review of Vector Algebra and Vector Calculus Operations

Review of Vector Algebra and Vector Calculus Operations Revew of Vecto Algeba and Vecto Calculus Opeatons Tpes of vaables n Flud Mechancs Repesentaton of vectos Dffeent coodnate sstems Base vecto elatons Scala and vecto poducts Stess Newton s law of vscost

More information

Physics 1501 Lecture 19

Physics 1501 Lecture 19 Physcs 1501 ectue 19 Physcs 1501: ectue 19 Today s Agenda Announceents HW#7: due Oct. 1 Mdte 1: aveage 45 % Topcs otatonal Kneatcs otatonal Enegy Moents of Ineta Physcs 1501: ectue 19, Pg 1 Suay (wth copason

More information

Harmonic oscillator approximation

Harmonic oscillator approximation armonc ocllator approxmaton armonc ocllator approxmaton Euaton to be olved We are fndng a mnmum of the functon under the retrcton where W P, P,..., P, Q, Q,..., Q P, P,..., P, Q, Q,..., Q lnwgner functon

More information

Kinematics in 2-D (II)

Kinematics in 2-D (II) Kinematics in 2-D (II) Unifom cicula motion Tangential and adial components of Relative velocity and acceleation a Seway and Jewett 4.4 to 4.6 Pactice Poblems: Chapte 4, Objective Questions 5, 11 Chapte

More information

Characterizations of Slant Helices. According to Quaternionic Frame

Characterizations of Slant Helices. According to Quaternionic Frame Appled Mathematcal Scence, Vol. 7, 0, no. 75, 79-78 HIKARI Ltd, www.m-hka.com http://dx.do.og/0.988/am.0.557 Chaactezaton of Slant Helce Accodng to Quatenonc Fame Hüeyn KOCAYİĞİT and Beyza Betül PEKACAR

More information

Rotating Disk Electrode -a hydrodynamic method

Rotating Disk Electrode -a hydrodynamic method Rotatng Dsk Electode -a hdodnamc method Fe Lu Ma 3, 0 ente fo Electochemcal Engneeng Reseach Depatment of hemcal and Bomolecula Engneeng Rotatng Dsk Electode A otatng dsk electode RDE s a hdodnamc wokng

More information

VECTOR MECHANICS FOR ENGINEERS: STATICS

VECTOR MECHANICS FOR ENGINEERS: STATICS 4 Equilibium CHAPTER VECTOR MECHANICS FOR ENGINEERS: STATICS Fedinand P. Bee E. Russell Johnston, J. of Rigid Bodies Lectue Notes: J. Walt Ole Texas Tech Univesity Contents Intoduction Fee-Body Diagam

More information

CHAPTER 4 TWO-COMMODITY CONTINUOUS REVIEW INVENTORY SYSTEM WITH BULK DEMAND FOR ONE COMMODITY

CHAPTER 4 TWO-COMMODITY CONTINUOUS REVIEW INVENTORY SYSTEM WITH BULK DEMAND FOR ONE COMMODITY Unvety of Petoa etd Van choo C de Wet 6 CHAPTER 4 TWO-COMMODITY CONTINUOU REVIEW INVENTORY YTEM WITH BULK DEMAND FOR ONE COMMODITY A modfed veon of th chapte ha been accepted n Aa-Pacfc Jounal of Opeatonal

More information

Tensor. Syllabus: x x

Tensor. Syllabus: x x Tenso Sllabus: Tenso Calculus : Catesan tensos. Smmetc and antsmmetc tensos. Lev Vvta tenso denst. Pseudo tensos. Dual tensos. Dect poduct and contacton. Dads and dadc. Covaant, Contavaant and med tensos.

More information

Chapter 23: Electric Potential

Chapter 23: Electric Potential Chapte 23: Electc Potental Electc Potental Enegy It tuns out (won t show ths) that the tostatc foce, qq 1 2 F ˆ = k, s consevatve. 2 Recall, fo any consevatve foce, t s always possble to wte the wok done

More information

Test 2 phy a) How is the velocity of a particle defined? b) What is an inertial reference frame? c) Describe friction.

Test 2 phy a) How is the velocity of a particle defined? b) What is an inertial reference frame? c) Describe friction. Tet phy 40 1. a) How i the velocity of a paticle defined? b) What i an inetial efeence fae? c) Decibe fiction. phyic dealt otly with falling bodie. d) Copae the acceleation of a paticle in efeence fae

More information

FI 2201 Electromagnetism

FI 2201 Electromagnetism FI Electomagnetim Aleande A. Ikanda, Ph.D. Phyic of Magnetim and Photonic Reeach Goup ecto Analyi CURILINEAR COORDINAES, DIRAC DELA FUNCION AND HEORY OF ECOR FIELDS Cuvilinea Coodinate Sytem Cateian coodinate:

More information

COMPLEMENTARY ENERGY METHOD FOR CURVED COMPOSITE BEAMS

COMPLEMENTARY ENERGY METHOD FOR CURVED COMPOSITE BEAMS ultscence - XXX. mcocd Intenatonal ultdscplnay Scentfc Confeence Unvesty of skolc Hungay - pl 06 ISBN 978-963-358-3- COPLEENTRY ENERGY ETHOD FOR CURVED COPOSITE BES Ákos József Lengyel István Ecsed ssstant

More information

OP = OO' + Ut + Vn + Wb. Material We Will Cover Today. Computer Vision Lecture 3. Multi-view Geometry I. Amnon Shashua

OP = OO' + Ut + Vn + Wb. Material We Will Cover Today. Computer Vision Lecture 3. Multi-view Geometry I. Amnon Shashua Comuer Vson 27 Lecure 3 Mul-vew Geomer I Amnon Shashua Maeral We Wll Cover oa he srucure of 3D->2D rojecon mar omograh Marces A rmer on rojecve geomer of he lane Eolar Geomer an Funamenal Mar ebrew Unvers

More information

Scattering of two identical particles in the center-of. of-mass frame. (b)

Scattering of two identical particles in the center-of. of-mass frame. (b) Lecture # November 5 Scatterng of two dentcal partcle Relatvtc Quantum Mechanc: The Klen-Gordon equaton Interpretaton of the Klen-Gordon equaton The Drac equaton Drac repreentaton for the matrce α and

More information

CSU ATS601 Fall Other reading: Vallis 2.1, 2.2; Marshall and Plumb Ch. 6; Holton Ch. 2; Schubert Ch r or v i = v r + r (3.

CSU ATS601 Fall Other reading: Vallis 2.1, 2.2; Marshall and Plumb Ch. 6; Holton Ch. 2; Schubert Ch r or v i = v r + r (3. 3 Eath s Rotaton 3.1 Rotatng Famewok Othe eadng: Valls 2.1, 2.2; Mashall and Plumb Ch. 6; Holton Ch. 2; Schubet Ch. 3 Consde the poston vecto (the same as C n the fgue above) otatng at angula velocty.

More information

3. Perturbation of Kerr BH

3. Perturbation of Kerr BH 3. Petubation of Ke BH hoizon at Δ = 0 ( = ± ) Unfotunately, it i technically fomidable to deal with the metic petubation of Ke BH becaue of coupling between and θ Nevethele, thee exit a fomalim (Newman-Penoe

More information

Goodness-of-fit for composite hypotheses.

Goodness-of-fit for composite hypotheses. Section 11 Goodness-of-fit fo composite hypotheses. Example. Let us conside a Matlab example. Let us geneate 50 obsevations fom N(1, 2): X=nomnd(1,2,50,1); Then, unning a chi-squaed goodness-of-fit test

More information

Physics 202, Lecture 2. Announcements

Physics 202, Lecture 2. Announcements Physcs 202, Lectue 2 Today s Topcs Announcements Electc Felds Moe on the Electc Foce (Coulomb s Law The Electc Feld Moton of Chaged Patcles n an Electc Feld Announcements Homewok Assgnment #1: WebAssgn

More information

LASER ABLATION ICP-MS: DATA REDUCTION

LASER ABLATION ICP-MS: DATA REDUCTION Lee, C-T A Lase Ablaton Data educton 2006 LASE ABLATON CP-MS: DATA EDUCTON Cn-Ty A. Lee 24 Septembe 2006 Analyss and calculaton of concentatons Lase ablaton analyses ae done n tme-esolved mode. A ~30 s

More information

1 cos. where v v sin. Range Equations: for an object that lands at the same height at which it starts. v sin 2 i. t g. and. sin g

1 cos. where v v sin. Range Equations: for an object that lands at the same height at which it starts. v sin 2 i. t g. and. sin g SPH3UW Unt.5 Projectle Moton Pae 1 of 10 Note Phc Inventor Parabolc Moton curved oton n the hape of a parabola. In the drecton, the equaton of oton ha a t ter Projectle Moton the parabolc oton of an object,

More information

Physics Exam II Chapters 25-29

Physics Exam II Chapters 25-29 Physcs 114 1 Exam II Chaptes 5-9 Answe 8 of the followng 9 questons o poblems. Each one s weghted equally. Clealy mak on you blue book whch numbe you do not want gaded. If you ae not sue whch one you do

More information

Chapter 5 Force and Motion

Chapter 5 Force and Motion Chapte 5 Foce and Motion In chaptes 2 and 4 we have studied kinematics i.e. descibed the motion of objects using paametes such as the position vecto, velocity and acceleation without any insights as to

More information

4 SingularValue Decomposition (SVD)

4 SingularValue Decomposition (SVD) /6/00 Z:\ jeh\self\boo Kannan\Jan-5-00\4 SVD 4 SngulaValue Decomposton (SVD) Chapte 4 Pat SVD he sngula value decomposton of a matx s the factozaton of nto the poduct of thee matces = UDV whee the columns

More information

Q. Obtain the Hamiltonian for a one electron atom in the presence of an external magnetic field.

Q. Obtain the Hamiltonian for a one electron atom in the presence of an external magnetic field. Syed Ashad Hussain Lectue Deatment of Physics Tiua Univesity www.sahussaintu.wodess.com Q. Obtain the Hamiltonian fo a one electon atom in the esence of an extenal magnetic field. To have an idea about

More information

Precision Spectrophotometry

Precision Spectrophotometry Peciion Spectophotomety Pupoe The pinciple of peciion pectophotomety ae illutated in thi expeiment by the detemination of chomium (III). ppaatu Spectophotomete (B&L Spec 20 D) Cuvette (minimum 2) Pipet:

More information

Question 1: The dipole

Question 1: The dipole Septembe, 08 Conell Univesity, Depatment of Physics PHYS 337, Advance E&M, HW #, due: 9/5/08, :5 AM Question : The dipole Conside a system as discussed in class and shown in Fig.. in Heald & Maion.. Wite

More information

POWER RATINGS AND LOSSES ESTIMATION OF A SWITCHED RELUCTANCE MOTOR FOR ELECTRIFIED RAILWAY APPLICATIONS

POWER RATINGS AND LOSSES ESTIMATION OF A SWITCHED RELUCTANCE MOTOR FOR ELECTRIFIED RAILWAY APPLICATIONS POER RATIGS AD LOSSES ESTIMATIO OF A SITCHED RELUCTACE MOTOR FOR ELECTRIFIED RAILAY APPLICATIOS Mohammad Shafan Fahad Shahna hafan@tabzuac fahadhahna@yahoocom Cente of Excellence fo Mechatonc, Unvety of

More information

Physics 201 Lecture 4

Physics 201 Lecture 4 Phscs 1 Lectue 4 ltoda: hapte 3 Lectue 4 v Intoduce scalas and vectos v Peom basc vecto aleba (addton and subtacton) v Inteconvet between atesan & Pola coodnates Stat n nteestn 1D moton poblem: ace 9.8

More information

Pythagorean triples. Leen Noordzij.

Pythagorean triples. Leen Noordzij. Pythagorean trple. Leen Noordz Dr.l.noordz@leennoordz.nl www.leennoordz.me Content A Roadmap for generatng Pythagorean Trple.... Pythagorean Trple.... 3 Dcuon Concluon.... 5 A Roadmap for generatng Pythagorean

More information