|
|
- しらん おおふさ
- 7 years ago
- Views:
Transcription
1 2004 TV Indexing Index Auto-Making Soccer Video Digests : U043-0 Katsunori Kawaguchi
2 RGB CMY HSV YCC
3 Index
4
5 RGB CYM RGB
6
7 3.1 Index
8 1 1.1 CS BS TV 1.2 Indexing [1] [4] [5] [6] [7] [8] TV 2 TV TV 7
9 1 Indexing Index
10 x,y 2 (brightness) (gray level value) f(x, y) = g x,y g x,y T x,y
11 2 2.1: (raster) (raster scan image) 2.2: 10
12 2 2.2 (color model,color base) RGB RGB (Red) (Green) (Blue) (additive mixing) 3 R G B (8 ) CMY CYM RGB (cyan) (magenta) (yellow) (subtractive mixing) 3 (black) CMYK 2.4 RGB CMY C = 255 R, M = 255 G, Y = 255 B 2.3: RGB 2.4: CYM 11
13 HSV HSV (Hue angle) (Saturation) (Value) HSV H 0 2π 0 π/3 2π/3 π 4π/3 5π/3 2π 2.5 S V (Value) (Lightness) HSL HLS RGB HSV V = max(r, G, B) { 0 (max(r, G, B) = 0 ) S = 1 min(r, G, B)/ max(r, G, B) ( ) H = 0 (S = 0 ) (G B)/(max(R, G, B) min(r, G, B)) (max(r, G, B) = R ) (B R)/(max(R, G, B) min(r, G, B)) (max(r, G, B) = G ) (R G)/(max(R, G, B) min(r, G, B)) (max(r, G, B) = B ) 2.5: 12
14 YCC YCC NTSC(National Television System Committee) (Y,CIE Y ) (Cb) (Cr) YCbCr YUV YIQ RGB YCC Y = r g b Cb = r g b Cr = r g b M N (density histgram) 2.6,
15 2 2.6: 2.7: RGB (binary image) 2 2 CPU (Affine transformation) 14
16 (x,y) (X,Y) [ ] [ ] X Y W = x y 1 a d 0 b e 0 c f 0 X = ax + by + c, Y = dx + ey + f (x,y,z) (X,Y,Z) 3 [ ] [ ] X Y Z W = x y z 1 a e i 0 b f j 0 c g k 0 d h l (x,y,(0)) (X,Y,Z) 3 Z (X,Y ) 4 15
17 2 [ ] [ ] X Y Z W = x y 0 1 a d p 0 b e q 0 z 1 z 2 z 3 0 c f r 0 X = ax + by + c px + qy + r, Y = dx + ey + f px + qy + r 2.8:
18 2! "$# % 2.9: (pattern matching) (template matching) 17
19 2 P i = (P i,1, P i,2,..., P i,n ) P T = (P T,1, P T,2,..., P T,n ) D u = n (P i,k P T,k ) 2 k=0!#"$!&%')( * 2.10: ( 2.10 ) 18
20 Index Index
21 3 Indexing Index 3. indexing!) * "$#&%('! ;< 8 "$#&%(':8 354 '7698 +,.-0/ : 3.2: 20
22 3 3.2 # #,+ %$&'( -/ "! 67 8:9<;= )%*% 3.3: Indexing 3. Index 4. 1,2 3,4 Index M 1. M S 1, S 2,..., S n T T 1, T 2,..., T n M = {S 1, S 2,..., S n } T = {T 1, T 2,..., T n } 21
23 3 2. Indexing S i Index I Si 1, I Si 2,..., I Si h S i = {I Si 1, I Si 2,..., I Si h} Index O 1, O 2,..., O l 3. P (S i ) P (S i ) = P ({I Si 1, I Si 2,..., I Si h}) = {I Si 1, I Si 2,..., I Si g,..., I Si h} {O 1, O 2,..., O k,..., O l } IndexI Si g Index O k m t 4. t P (S i ) S 1, S 2,..., S m m X P (S i ) m = {S r1, S r2,..., S ri,..., S rj } { X (k {r1, r 2,..., r j }) P (S k ) < X ( ) r i < r i+1 t j T rk k=1 3.3 Index Indexing Index
24 : Index 3.4: 23
25 4 TV Index TV [1][3] TV 4.1: 24
26 TV TV 4.2 Indexing Indexing Indexing 10% 50% TV 4.2: 25
27 4 4.2 TV 4.3 Indexing Indexing Index 4.3: 26
28 5 Indexing TV Microsoft VisualC (width) 320,360,640,720 dot (height) 240,480 dot 29.97fps 24bit Color VfW(Video for Windows) Avi M F 1, F 2,..., F framemax F i 27
29 F t F t+1 RGB S(t) k 5.1 M S 1, S 2,..., S n S i F j, F j+1,..., F k j = S i ST, k = S i ED S i ED + 1 = S i+1 ST 255 R(t) = r t+1 (i) r t (i) i=0 S(t) = R(t) + G(t) + B(t) r t (i) : F t r i S(t) k k = M = {S 1, S 2,..., S n } 28
30 S i = {F j, F j+1,..., F k } 5 = {F Si ST,..., F Si ED} 5.1: Y Y < Y cut Y > 255 Y cut Y cut = 40 F t h t h h 20 % H cut i 5.2 h t (i) : F t i Y cut Y 255 Y cut h(i) = framemax t=1 h t (i) 29
31 /. YX -W 0Z^ H cut = MAX(h(i)) 0.2(0 i 359) 5 h(i) H cut i H feild H feild A B CDEF 6b 798 c9d : e ; f < g = h > i 254 \5] `5a 0Z^ 132 [3\ _3` 0Z^ G HG IG JG KLG KMG KNG LKG LOG L PG HGG HHG!" H!I"G # #$&%('*)+,?#@#Q&R(S*TUV 5.2:
32 5 4.3 H feild H feild F Av F CH 6 60 (i 1) H 60 i(1 i 6) 6 8 H(f) f H Av S ted F Av = h i (j H feild ) /(S t ED S t ST + 1) i=s t ST S t ED 1 F CH = h i (j H feild ) h i+1 (j) /(S t ED S t ST ) i=s t ST S t ED H Av = i=s tst H(i) /(S t ED S t ST + 1) H feild F Av F CH H Av F Av,F CH,H Av k 1,k 2,k : F Av k 1 2 : F Av k 2, F CH < k 3, H Av k 4 2 k 1 = 20000, k 2 = 50000, k 3 = 500, k 4 = pass 1 2-pass
33 5 5.3: 5.1: F Av F CH H Av H feild 2 (r, g, b) = (255, 255, 255)
34 5 5.4: (h, w) (H, W ) 3 Ah + Bw + 1 Dh + Ew + 1 H = C, W = F P h + Qw + 1 P h + Qw Hough 2 Affine?? Y 2 S l e 5.3 e = 4πS l 2 33
35 5 5.5: 5.6: s
36 % $ # "! & ' 5 5.2: H(m) W (m) :
37 5 5.7: 5.8: Indexing Indexing 36
38 5 5.9: VTR VTR [d 1, d 2, d 3, d 4, d 5 ] (d 1, d 2 ) : (H, W ) (d 3, d 4 ) : (h, w) d 5 : 37
39 5 5.10: 5.11: 38
40 5 5.3 Index 1. (a) 3m (b) (c) 2. (a) (b) (c) 3. (a) 4. (a) (b) (c)
41 5 V s s A s(n) s 1 0 n W (n) W (n) W V s (s = 0, 1,..., scene MAX ) A s(n) = 1 ( n V s ) = 0 ( V t s W (n) = A s(n) W = Av(W (n) ) n Indexing m Indexing 40
42 5 5.4: 1 int[2] time[2] int int double double double double int double double double double int double double double double CK(IN) CK(OUT) FK(IN) FK(OUT) GK(IN) GK(OUT) SI(IN) SI(OUT) bool bool bool bool bool bool bool bool double GK int double 41
43 : % %
44 : % 52.2% 80.0% 6.3: % 92.0% % 88.6% % 87.5% % 88.2% %
45 6 6.4: % 67.5% % 53.5% % 84.0% % 68.0% % 68.3% % 62.5% %
46 6 6.5: % 87.5% % 89.1% % 88.3% % 86.2% 6.6: % 67.0% % 87.6% % 77.3% % 80.5% 2 > FK CK FK 4 30% 6.2 Indexing 2 Index 6.1 Index 45
47 6 Indexing (1) Index Index Index Index (2) Index Index Indexing Indexing (3) Index Index 46
48 ' & 6 C +,.- (*),.- / "!$#% $: < >@? <?FEHG = =BADC C ; $: < >@? <?FEHG I =KJ I =JLA INM ILM ILM 6.1: 47
49 7 7.1 Index Indexing OPTA [10] 48
50 7 7.1: 7.2: 49
51 [1],, 2001,Feb 2002 [2],, 2003,Feb 2004 [3],, 2003,Feb 2004 [4],,,, ,Feb 2002 [5],,,, TECHNICAL REPORT OF IEICE. PRMU ,Jan 2001 [6],,,, TECHNICAL REPORT OF IEICE. PRMU ,Jan 2001 [7],,,, TECHNICAL REPORT OF IEICE. PRMU ,Jan 2001 [8],,, - -, TECHNICAL REPORT OF IEICE. IE ,PRMU ,MVE ,Jul 2001 [9],V.V.Vinod, - -, D-ll Vol. J81-D-ll No.9,Sep
52 7 [10] OPTA INDEX 51
53 OB OB OB M2 M
131 71 7 1 71 71 71 71 71 71 71 71 71 71 7 1 71 71 71 71 71 71 71 71 7 1 71 7 1 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 7 1 71 71 71 71 71 71 71 71 71 7 1 71 71 71 71 71 71 71 7 1 71 7 1 71
More informationl3.pdf
3 (R) (G) (B) 3 RGB PCCS 3 CIE XYZ xy CIE LUV CIE LAB srgbhsvyiqycbcr 3.1 3.1.1 3.1 24 3 3.1 3.2 380 nm 780 nm 650 nm 400 nm 3.2 3.1.2 3.3 3.2 25 3.3 3.4 2 LMS 3 3.4 L M L 3.2 PCCS CIE XYZCIE LUVCIE 26
More information●70974_100_AC009160_KAPヘ<3099>ーシス自動車約款(11.10).indb
" # $ % & ' ( ) * +, -. / 0 1 2 3 4 5 6 7 8 9 : ; < = >? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y " # $ % & ' ( ) * + , -. / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B
More informationMicrosoft Word - 触ってみよう、Maximaに2.doc
i i e! ( x +1) 2 3 ( 2x + 3)! ( x + 1) 3 ( a + b) 5 2 2 2 2! 3! 5! 7 2 x! 3x! 1 = 0 ",! " >!!! # 2x + 4y = 30 "! x + y = 12 sin x lim x!0 x x n! # $ & 1 lim 1 + ('% " n 1 1 lim lim x!+0 x x"!0 x log x
More informationコンピュータグラフィックス - 第4回 色彩の表現
.. 4 2013 10 9 ( ) 2013 10 9 1 / 22 3 3 3 ( ) 2013 10 9 2 / 22 380 nm 780 nm 1 nm = 10 9 m ( ) 2013 10 9 3 / 22 3 3 (S M L ) 3 3 3 ( ) 2013 10 9 4 / 22 加法混色 光の 3 原色を組み合わせることで 様々な色を表現できる 光を重ねて別の色を作ることを加法混色と呼ぶ
More information(Visual Secret Sharing Scheme) VSSS VSSS 3 i
13 A Visual Secret Sharing Scheme for Continuous Color Images 10066 14 8 (Visual Secret Sharing Scheme) VSSS VSSS 3 i Abstract A Visual Secret Sharing Scheme for Continuous Color Images Tomoe Ogawa The
More information1 2 3 X-Rite, Incorporated 1998 ALL RIGHTS RESERVED
1 2 3 www.x-rite.com X-Rite, Incorporated 1998 ALL RIGHTS RESERVED 1 1 The Color Guide and Glossary input 2 Color Communication 3 The Color Guide and Glossary 4 Color Communication 5 The Color Guide and
More information色覚(初組4).pm
Vol.21 No.8 2002 909 3 2 1 1 2 2.1 1 5 1 95 5 1 L M S 3 2A 1 1 http://www.nig.ac.jp/labs/devgen/mou.html 910 Vol.21 No.8 2002 R G B C A H R G B C B R 2 33 3 1 3 2 3 2A Vol.21 No.8 2002 911 1 2 X 584 300
More information画像情報処理の基礎
AI artificial intelligencedeep learning; OpenCV C MATLAB Python ii 1 1 10 11 14 2019 3 1. 1.1... 1 1.2... 2 1.2.1 3... 2 1.2.2... 2 1.2.3... 2 1.3... 3 1.3.1 RGB... 3 1.3.2 YIQ... 3 1.3.3 HSI... 3 1.3.4
More informationデジタルビデオ入門
f r o m t h e A d o b e D i g i t a l V i d e o G r o u p A D V P r i m e r : I N T R O D U C T I O N A N D C O N T E N T S DV 2 A D V P r i m e r : V I D E O B A S I C S 1 1 0 10 1 2 2 DVD DTV TV TV TV
More information†ı25”Y„o-PDF.ren
12,000 10,000 8,000 6,000 4,000 2,000 0 1998 1999 2000 2001 2002 2003 2004 1,200 1,000 800 600 400 200 0 1998 1999 2000 2001 2002 2003 2004 $ "! ''" '' ''$ ''% ''& '''! " ' & % $ "! ''" ' '$ '% '& ''!
More information76
! # % & % & %& %& " $ 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 % & &! & $ & " & $ & # & ' 91 92 $ % $'%! %(% " %(% # &)% & 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 !$!$ "% "%
More information撮 影
DC cathode ray tube, 2.2 log log log + log log / / / A method determining tone conversion characteristics of digital still camera from two pictorial images Tone conversion characteristic Luminance
More information! & # # w w w w w w w w l & w_ # w_ w # w w w # w w # w w # w w w w bw w bw w bw w w bw w b w w_ l !!!!!! 6!!!! 6 ' ' ' ' ' ' ' ' ' ' ' '! ' ' ' ' ' ' ' ' ' ' ' ' ' '! ' ' ' ' ' ' ' ' ' ' '
More information7 27 7.1........................................ 27 7.2.......................................... 28 1 ( a 3 = 3 = 3 a a > 0(a a a a < 0(a a a -1 1 6
26 11 5 1 ( 2 2 2 3 5 3.1...................................... 5 3.2....................................... 5 3.3....................................... 6 3.4....................................... 7
More information欧州特許庁米国特許商標庁との共通特許分類 CPC (Cooperative Patent Classification) 日本パテントデータサービス ( 株 ) 国際部 2019 年 7 月 31 日 CPC 版が発効します 原文及び詳細はCPCホームページのCPC Revision
欧州特許庁米国特許商標庁との共通特許分類 CPC (Cooperative Patent Classification) 日本パテントデータサービス ( 株 ) 国際部 2019 年 7 月 31 日 CPC 2019.08 版が発効します 原文及び詳細はCPCホームページのCPC Revisions(CPCの改訂 ) をご覧ください https://www.cooperativepatentclassification.org/cpcrevisions/noticeofchanges.html
More information- 1 - - 2 - 320 421 928 1115 12 8 116 124 2 7 4 5 428 515 530 624 921 1115 1-3 - 100 250-4 - - 5 - - 6 - - 7 - - 8 - - 9 - & & - 11 - - 12 - GT GT - 13 - GT - 14 - - 15 - - 16 - - 17 - - 18 - - 19 - -
More information顔認識の為のリアルタイム特徴抽出
... 3... 4... 5... 5.... 5.... 6..... 6..... 8.... 8.... 8... 9.... 9..... 9..... 10.....11..... 12.... 17..... 17.... 19..... 19..... 21..... 23..... 24..... 25.... 26..... 26..... 26... 29.... 29....
More information2
1 2 10 14 945 3000 2012 3 10 4 5 6 7 8 9 10 11 12 2011 11 21 12301430 (1215 ) 13 6 27 17 () ( ) ( ) (112360) 2 (1157) (119099) ((11861231) )( ) (11641205) 3 (1277) 3 4 (1558) (1639)() 12 (1699)( ) 7 (1722)
More information32 1 7 1 20 ( ) [18 30] [21 00] 2 3 ( ( ) ) ( ) 4 1 2 95 ( 7 3 2 ) 1 2 3 2 a b
31 1 7 1 ( ) [18 35] [20 40] 2 3 ( ( ) ) ( ) 4 1 2 1 22 1 2 a b T T A c d 32 1 7 1 20 ( ) [18 30] [21 00] 2 3 ( ( ) ) ( ) 4 1 2 95 ( 7 3 2 ) 1 2 3 2 a b 7 1 ( 34 ) 1 7 2 13 ( ) [18 20] [20 00] 2 4 7 3
More information掲示用ヒート表 第34回 藤沢市長杯 2017
34 8 4 2 Round 1 Round 2 SEMI FINAL 30 16 8 H1 H5 H1 H1 Red 12401821 2 Red 12601360 2 1-1 Red 12501915 1 1-1 Red 12501915 4 White 12900051 4 White 12600138 3 3-1 White 12802412 2 3-1 White 12801091 1 Yellow
More informationさくらの個別指導 ( さくら教育研究所 ) A AB A B A B A AB AB AB B
1 1.1 1.1.1 1 1 1 1 a a a a C a a = = CD CD a a a a a a = a = = D 1.1 CD D= C = DC C D 1.1 (1) 1 3 4 5 8 7 () 6 (3) 1.1. 3 1.1. a = C = C C C a a + a + + C = a C 1. a a + (1) () (3) b a a a b CD D = D
More information1.1 EPS... 3 1.2 EPS... 3 1.2.1... 3 1.2.2... 4 1.3... 5 2.1 BMP... 6 2.2 BMP... 6 2.2.1... 6 2.2.2... 6 2.2.3 (Appendix )... 7 3.1 TIFF... 8 3.2 TIFF... 8 3.2.1... 8 3.2.2... 9 3.2.3 (Appendix )... 9
More informationMicrosoft Word - =?iso-2022-jp?B?SFAbJEJNUSEhIUpMPkEwRn4kaiFLGyhCNDAbJEJCZUZ8S1wbKEI=?= =?iso-2022-jp?B?GyRCP00kTkNmOXE0USFKI1cjUCFLRHM9UE1RGyhCKBskQj0kGyhCLg==?= =?iso-2022-jp?B?ZG9j?=
40 COE-CAS RA 2005 10 21 COE 40 2005 80 1990 1 1990 1995 50 21 3 1 (2005 ) 1 2 1998 11 80 ODA 3 2001 (2002 ) (2003 9 ) (2003 10 ) (2004 8 ) Voice SAPIO 4 5 (1932 ) (1932 ) (1933 ) (1948 ) (1930 ) ( 1971
More informationr 1 m A r/m i) t ii) m i) t B(t; m) ( B(t; m) = A 1 + r ) mt m ii) B(t; m) ( B(t; m) = A 1 + r ) mt m { ( = A 1 + r ) m } rt r m n = m r m n B
1 1.1 1 r 1 m A r/m i) t ii) m i) t Bt; m) Bt; m) = A 1 + r ) mt m ii) Bt; m) Bt; m) = A 1 + r ) mt m { = A 1 + r ) m } rt r m n = m r m n Bt; m) Aert e lim 1 + 1 n 1.1) n!1 n) e a 1, a 2, a 3,... {a n
More information1/68 A. 電気所 ( 発電所, 変電所, 配電塔 ) における変圧器の空き容量一覧 平成 31 年 3 月 6 日現在 < 留意事項 > (1) 空容量は目安であり 系統接続の前には 接続検討のお申込みによる詳細検討が必要となります その結果 空容量が変更となる場合があります (2) 特に記載
1/68 A. 電気所 ( 発電所, 変電所, 配電塔 ) における変圧器の空き容量一覧 平成 31 年 3 月 6 日現在 < 留意事項 > (1) 空容量は目安であり 系統接続の前には 接続検討のお申込みによる詳細検討が必要となります その結果 空容量が変更となる場合があります (2) 特に記載のない限り 熱容量を考慮した空き容量を記載しております その他の要因 ( 電圧や系統安定度など ) で連系制約が発生する場合があります
More informationD端子 RGBコンバータ ユーザーズマニュアル
LDC-RGB V0W D-COMPONENT to RGB Converter D -RGB LDC-RGB ... 1... 4... 4...5... 6... 6... 8... 13... 14... 14... 17... 17... 19... 0... 4... 6... 9... 31... 35... 37... 39... 4... 44... 44... 48 D... 54...
More information-1-1 1 1 1 1 12 31 2 2 3 4
2007 -1-1 1 1 1 1 12 31 2 2 3 4 -2-5 6 CPU 3 Windows98 1 -3-2. 3. -4-4 2 5 1 1 1 -5- 50000 50000 50000 50000 50000 50000 50000 50000 50000 50000-6- -7-1 Windows 2 -8-1 2 3 4 - - 100,000 200,000 500,000
More informationx = a 1 f (a r, a + r) f(a) r a f f(a) 2 2. (a, b) 2 f (a, b) r f(a, b) r (a, b) f f(a, b)
2011 I 2 II III 17, 18, 19 7 7 1 2 2 2 1 2 1 1 1.1.............................. 2 1.2 : 1.................... 4 1.2.1 2............................... 5 1.3 : 2.................... 5 1.3.1 2.....................................
More information21 e-learning Development of Real-time Learner Detection System for e-learning
21 e-learning Development of Real-time Learner Detection System for e-learning 1100349 2010 3 1 e-learning WBT (Web Based training) e-learning LMS (Learning Management System) LMS WBT e-learning e-learning
More information( )
NAIST-IS-MT0051071 2002 2 8 ( ) 3 2,,,, 3, NAIST-IS- MT0051071, 2002 2 8. i Automation of the Soccer Game Analysis 3 Yasushi Nakagawa Abstract Recently it has become popular to deliver the video data on
More information★結果★ 藤沢市長杯 掲示用ヒート表
AA 35 Round 1 8 4 Round 2 28 16 SEMI FINAL H1 H5 H1 H1 Red 12802015 1 Red 12802109 1 1-1 Red 12802015 2 1-1 Red 12702346 White 12800232 2 White 12702406 3 3-1 White 12702346 1 3-1 White 12802109 Yellow
More informationMicrosoft Word - 5MS.doc
5 5.1 mass spectrometer electron impact, EI 5.1 :;"< 789 =>? *!"#$%& '%&(),,,-./ 0.12%3456 :;"@AB CDEFG:;"HIJK@LMN :;"@HIOPQ0RST6 5.1. 70 ev molecular ion #"$%& M M e!"!"'() #" m/z ; m = z = 1 mass spectrum,
More informationmain.dvi
A 1/4 1 1/ 1/1 1 9 6 (Vergence) (Convergence) (Divergence) ( ) ( ) 97 1) S. Fukushima, M. Takahashi, and H. Yoshikawa: A STUDY ON VR-BASED MUTUAL ADAPTIVE CAI SYSTEM FOR NUCLEAR POWER PLANT, Proc. of FIFTH
More informationLVC-TV_V03 USB TV TUNER + CAPTURE UNIT LVC-TV LVC-TV
LVC-TV_V03 USB TV TUNER + CAPTURE UNIT LVC-TV LVC-TV ... 1... 2... 4... 5... 5... 6... 6... 8... 9... 9... 10... 11 Windows Me... 11 Windows 98... 13 Windows 2000... 16... 20... 20... 23 PowerVCR II...
More informationAbstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the imag
2004 RGB A STUDY OF RGB COLOR INFORMATION AND ITS APPLICATION 03R3237 Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One
More information飯能市と名栗村の新しいまちづくり計画に関する住民意識調査
- 1 - - 2-299 299 299 - 3-299 299 - 4-30 299 299 JR - 5-10 299 299 12 JR 2K JR - 6 - R299 R299 299 27 299 299 JR - 7 - JR 50 1 2 20 299 299 - 8-299 --- 299 70 299 - 9-299 299 33 - 10 - TV 2/ 299 299 -
More informationf : R R f(x, y) = x + y axy f = 0, x + y axy = 0 y 直線 x+y+a=0 に漸近し 原点で交叉する美しい形をしている x +y axy=0 X+Y+a=0 o x t x = at 1 + t, y = at (a > 0) 1 + t f(x, y
017 8 10 f : R R f(x) = x n + x n 1 + 1, f(x) = sin 1, log x x n m :f : R n R m z = f(x, y) R R R R, R R R n R m R n R m R n R m f : R R f (x) = lim h 0 f(x + h) f(x) h f : R n R m m n M Jacobi( ) m n
More information1 Table 1: Identification by color of voxel Voxel Mode of expression Nothing Other 1 Orange 2 Blue 3 Yellow 4 SSL Humanoid SSL-Vision 3 3 [, 21] 8 325
社団法人人工知能学会 Japanese Society for Artificial Intelligence 人工知能学会研究会資料 JSAI Technical Report SIG-Challenge-B3 (5/5) RoboCup SSL Humanoid A Proposal and its Application of Color Voxel Server for RoboCup SSL
More informationmugensho.dvi
1 1 f (t) lim t a f (t) = 0 f (t) t a 1.1 (1) lim(t 1) 2 = 0 t 1 (t 1) 2 t 1 (2) lim(t 1) 3 = 0 t 1 (t 1) 3 t 1 2 f (t), g(t) t a lim t a f (t) g(t) g(t) f (t) = o(g(t)) (t a) = 0 f (t) (t 1) 3 1.2 lim
More informationTEAM WEAR 1
TEAM WEAR 1 2 TEAM WEAR BUSINESS WEAR 3 4 5 6 7 11 13 28 29 41 43 45 INDEX 3 4 5 6 z x c v b n 7 1 m 0, 2 3 4 5. z x c v b n m,. 0 1 2 3 4 5 8 z x c v b n m,. 9 1 0 2 3 4 5 z x c v b n m,. 0 1 2 3 4 5
More informationSXF Converter for DWG 2004/ SXFデータトランスレータ 2004 注意事項
SXF Converter for DWG 2004 SXF2004 (2005 ) 1... 1 1.1... 1 1.2 Windows DWG... 1 2 AutoCAD SXF... 1 2.1... 1 2.2... 1 2.3... 1 2.4... 1 2.5... 1 2.6... 2 2.7... 2 2.8... 3 2.9... 3 2.10... 4 2.11... 5 2.12...
More information曲面のパラメタ表示と接線ベクトル
L11(2011-07-06 Wed) :Time-stamp: 2011-07-06 Wed 13:08 JST hig 1,,. 2. http://hig3.net () (L11) 2011-07-06 Wed 1 / 18 ( ) 1 V = (xy2 ) x + (2y) y = y 2 + 2. 2 V = 4y., D V ds = 2 2 ( ) 4 x 2 4y dy dx =
More information7. y fx, z gy z gfx dz dx dz dy dy dx. g f a g bf a b fa 7., chain ule Ω, D R n, R m a Ω, f : Ω R m, g : D R l, fω D, b fa, f a g b g f a g f a g bf a
9 203 6 7 WWW http://www.math.meiji.ac.jp/~mk/lectue/tahensuu-203/ 2 8 8 7. 7 7. y fx, z gy z gfx dz dx dz dy dy dx. g f a g bf a b fa 7., chain ule Ω, D R n, R m a Ω, f : Ω R m, g : D R l, fω D, b fa,
More informationランダムウォークの境界条件・偏微分方程式の数値計算
B L06(2018-05-22 Tue) : Time-stamp: 2018-05-22 Tue 21:53 JST hig,, 2, multiply transf http://hig3.net L06 B(2018) 1 / 38 L05-Q1 Quiz : 1 M λ 1 = 1 u 1 ( ). M u 1 = u 1, u 1 = ( 3 4 ) s (s 0)., u 1 = 1
More informationtottori2013-print.key
1 / 152 3 / 152 2 / 152 4 / 152 5 / 152 7 / 152 6 / 152 8 / 152 9 / 152 11 / 152 Red: [R,G,B] = [255,0,0] Yellow [R,G,B] = [255, 255, 0] Magenta [R,G,B] = [255, 0, 255] W [R,G,B] = [ Green: [R,G,B] = [0,
More information14 CRT Color Constancy in the Conditions of Dierent Cone Adaptation in a CRT Display
14 CRT Color Constancy in the Conditions of Dierent Cone Adaptation in a CRT Display 1030281 2003 2 12 CRT [1] CRT. CRT von Kries PC CRT CRT 9300K CRT 6500K CRT CRT 9300K x y S L-2M x y von Kries S L-2M
More informationX G P G (X) G BG [X, BG] S 2 2 2 S 2 2 S 2 = { (x 1, x 2, x 3 ) R 3 x 2 1 + x 2 2 + x 2 3 = 1 } R 3 S 2 S 2 v x S 2 x x v(x) T x S 2 T x S 2 S 2 x T x S 2 = { ξ R 3 x ξ } R 3 T x S 2 S 2 x x T x S 2
More information13 0 1 1 4 11 4 12 5 13 6 2 10 21 10 22 14 3 20 31 20 32 25 33 28 4 31 41 32 42 34 43 38 5 41 51 41 52 43 53 54 6 57 61 57 62 60 70 0 Gauss a, b, c x, y f(x, y) = ax 2 + bxy + cy 2 = x y a b/2 b/2 c x
More information1 28 6 12 7 1 7.1...................................... 2 7.1.1............................... 2 7.1.2........................... 2 7.2...................................... 3 7.3...................................
More information2012年総選挙・テレビはどう伝えたか
2012 2013 1 2012 46 11 16 11 14 12 15 4 1 7 1 300 59.32 204 3 9 9 60 2 2010 5 67 11 19 30 3 19 23 11 20 21 23 24 23 12 12 4 12 4 14 14 13 3 10 2 40 2 10 1 40 18 23 11 27 22 28 16 40 5 11 21 12 13 12 3
More information熊本県数学問題正解
00 y O x Typed by L A TEX ε ( ) (00 ) 5 4 4 ( ) http://www.ocn.ne.jp/ oboetene/plan/. ( ) (009 ) ( ).. http://www.ocn.ne.jp/ oboetene/plan/eng.html 8 i i..................................... ( )0... (
More informationPowerPoint Presentation
2 3 4 HTML 5 Level.1 Markup Professional HTML 5 Level.2 Application Development Professional 5 6 7 8 9 http://www.html5exam.jp/ @html5cert https://www.facebook.com/html5exam http://www.pearsonvue.com/japan/registration/
More information時系列解析
B L12(2016-07-11 Mon) : Time-stamp: 2016-07-11 Mon 17:25 JST hig,, Excel,. http://hig3.net ( ) L12 B(2016) 1 / 24 L11-Q1 Quiz : 1 E[R] = 1 2, V[R] = 9 12 = 3 4. R(t), E[X(30)] = E[X(0)] + 30 1 2 = 115,
More information第三学年 総合的な学習の指導案(国際理解・英語活動)
NAT NAT NAT NAT NAT NAT All English NAT 20 One One One One One Show Time Silent Night Are You Sleeping? NAT NAT NAT NAT NAT What color do you like? ( NA ( ) Good afternoon, boys & girls. Good afternoon,
More information,2,4
2005 12 2006 1,2,4 iii 1 Hilbert 14 1 1.............................................. 1 2............................................... 2 3............................................... 3 4.............................................
More informationKLV-20AP2
2-021-355-11 (1) KLV-20AP2 2005 Sony Corporation ... 2... 3... 57 3 57 2 57 1 1 139 Input Select utton page 39 138 Memo utton page 38 / 133 Channel +/ uttons page 33 /133 Volume +/ uttons page 33 Power
More informationモノグラフ・中学生の世界 Vol.62
q w e r t y u i o!0!1!2 !3!4!5!6!7!8 !9 @0 @1 q w q q w e r q w e qw qw qw qw q qw q w e r q w q w z x qw q w e q w r t y u i o!0!1!2!3!4!5!6!7!8
More informations d
s d s s s q 1w d d d d s s q 1w q1w d s d d d d q1w d w w d d 4q 5q 6q 7q 8q 21q 41q 00q 10q 12q 70q 71q 81q 9q 31q d s d d s d s d d d d s d s q 1w q1w d d d d d
More information1 () 1-1 1-2 () 1-3 () 1-6 ( () ()) ( ) 1 2 1-4 1-1 1-5 1-5-1 1-2 1-2 3 4 1-3 ( ) 1-5-2 7 8 1-1 5 1-5-3 1-2 6 1-5-4 1-3 1-3 7 8 9 10 1-6 1-4 () () () () () 2 2-1 2-1-1 11 12 2-1-2 2-2 2-2-1 CD-R 2 CAD
More information1990 IMO 1990/1/15 1:00-4:00 1 N N N 1, N 1 N 2, N 2 N 3 N 3 2 x x + 52 = 3 x x , A, B, C 3,, A B, C 2,,,, 7, A, B, C
0 9 (1990 1999 ) 10 (2000 ) 1900 1994 1995 1999 2 SAT ACT 1 1990 IMO 1990/1/15 1:00-4:00 1 N 1990 9 N N 1, N 1 N 2, N 2 N 3 N 3 2 x 2 + 25x + 52 = 3 x 2 + 25x + 80 3 2, 3 0 4 A, B, C 3,, A B, C 2,,,, 7,
More information9 2 1 f(x, y) = xy sin x cos y x y cos y y x sin x d (x, y) = y cos y (x sin x) = y cos y(sin x + x cos x) x dx d (x, y) = x sin x (y cos y) = x sin x
2009 9 6 16 7 1 7.1 1 1 1 9 2 1 f(x, y) = xy sin x cos y x y cos y y x sin x d (x, y) = y cos y (x sin x) = y cos y(sin x + x cos x) x dx d (x, y) = x sin x (y cos y) = x sin x(cos y y sin y) y dy 1 sin
More informationFig. 1. Example of characters superimposed on delivery slip.
Extraction of Handwritten Character String Superimposed on Delivery Slip Data Ken-ichi MATSUO, Non-member, Katsuhiko UEDA, Non-member (Nara National College of Technology), Michio UMEDA, Member (Osaka
More informationuntitled
...1... 3 1... 3 2... 4 3... 4 4... 5...... 6 1... 6 2... 7 3... 8 4... 9 5... 10... 12 1... 12 2... 13 3... 14 4... 16...... 19 1... 19 2... 20 3... 22 4... 24...... 25... 26 1... 26 2... 26 3... 26......
More information.1 z = e x +xy y z y 1 1 x 0 1 z x y α β γ z = αx + βy + γ (.1) ax + by + cz = d (.1') a, b, c, d x-y-z (a, b, c). x-y-z 3 (0,
.1.1 Y K L Y = K 1 3 L 3 L K K (K + ) 1 1 3 L 3 K 3 L 3 K 0 (K + K) 1 3 L 3 K 1 3 L 3 lim K 0 K = L (K + K) 1 3 K 1 3 3 lim K 0 K = 1 3 K 3 L 3 z = f(x, y) x y z x-y-z.1 z = e x +xy y 3 x-y ( ) z 0 f(x,
More informationKLV-15AP2
2-590-527-01 (2) KLV-15AP2 2005 Sony Corporation ... 2... 3... 69 3 69 2 69 1 1 149 Input Select button page 49 148 Memo button page 48 / 143 Channel +/ buttons page 43 /143 Volume +/ buttons page 43 Power
More informationGE5000シリーズ ユーザーズマニュアル プリンタードライバー編
T-984P-6B MA1406-C 2015 6 15 3 1.Windows...3 2....6 3....7 3.1...7 4....9 4.1...9 4.2...12 4.3...14 4.4...16 4.5...18 4.6...20 4.7 GE5000...21 4.8 GE5000...22 4.9 GE5000-BR...24 4.10 GE5000-BR...25 4.11...27
More information[ ] Table
[] Te P AP OP [] OP c r de,,,, ' ' ' ' de,, c,, c, c ',, c mc ' ' m' c ' m m' OP OP p p p ( t p t p m ( m c e cd d e e c OP s( OP t( P s s t (, e e s t s 5 OP 5 5 s t t 5 OP ( 5 5 5 OAP ABP OBP ,, OP t(
More informationS: E: O: C: V : 5
( ) 2004 1 S: E: O: C: V : 5 1 1 2 2 2.1.................................... 2 2.2........................ 2 2.3........................... 3 3 7 3.1.................................... 7 3.2....................................
More information1 1 2 65
3 3 2000 6 14 2 30 4 2 1 1 2 65 1!?? < > 3 2 2 100 19 19 100 100 100 < > 19 2 2 2 2 < > 2000 2000 50 1945 5 50 1945 5 45 20 20 4 1945 4 5 5 5 100 50 20 5 2 20 5 20 5 5 6 20 6 19 5 5 6 5 6 2 20 6 21
More information1 8, : 8.1 1, 2 z = ax + by + c ax by + z c = a b +1 x y z c = 0, (0, 0, c), n = ( a, b, 1). f = n i=1 a ii x 2 i + i<j 2a ij x i x j = ( x, A x), f =
1 8, : 8.1 1, z = ax + by + c ax by + z c = a b +1 x y z c = 0, (0, 0, c), n = ( a, b, 1). f = a ii x i + i
More informationexample2_time.eps
Google (20/08/2 ) ( ) Random Walk & Google Page Rank Agora on Aug. 20 / 67 Introduction ( ) Random Walk & Google Page Rank Agora on Aug. 20 2 / 67 Introduction Google ( ) Random Walk & Google Page Rank
More information( )
18 10 01 ( ) 1 2018 4 1.1 2018............................... 4 1.2 2018......................... 5 2 2017 7 2.1 2017............................... 7 2.2 2017......................... 8 3 2016 9 3.1 2016...............................
More information1.1 ft t 2 ft = t 2 ft+ t = t+ t 2 1.1 d t 2 t + t 2 t 2 = lim t 0 t = lim t 0 = lim t 0 t 2 + 2t t + t 2 t 2 t + t 2 t 2t t + t 2 t 2t + t = lim t 0
A c 2008 by Kuniaki Nakamitsu 1 1.1 t 2 sin t, cos t t ft t t vt t xt t + t xt + t xt + t xt t vt = xt + t xt t t t vt xt + t xt vt = lim t 0 t lim t 0 t 0 vt = dxt ft dft dft ft + t ft = lim t 0 t 1.1
More information