ੱ㑆䉮䊚䊠䊆䉬䊷䉲䊢䊮䈮䈍䈔䉎䊜䊂䉞䉝䈱ᓎഀ॥঑গॽॣ‫ش‬३ঙথभ੍ର঺ভ३५ॸ঒ੲਾ્৾૛੡ଽોপ৾ ੲਾఐ৾ଢ଼஢ఐ঺ভ३५ॸ঒ੲਾ৾௧వ৑௿௏੸‫ڰ؝ڳ؝ڴڬڬڮ‬12䊜䊂䉞䉝䈮䉋䉎⴫⃻䈱ᱧผ•䊤䉴䉮䊷䈱ო↹•䊌䊏䊦䉴•⟠⊹⚕
•ᭉེ•ශ೚ᛛⴚ•ᤋ↹䊶౮⌀•㔚ା䊶㔚⹤•䊁䊧䊎䊶䊎䊂䉥•䉮䊮䊏䊠䊷䉺䉮䊮䊏䊠䊷䉺䈲䊜䊂䉞䉝䈪䈅䉎䋮䇸䉮䊮䊏䊠䊷䉺䉕䉿䊷䊦䈪䈲䈭䈒䊜䊂䉞䉝䈫䈚䈩䈫䉌䈋䉋䈉䇹䋨䊑䊧䊮䉻䊶䊨䊷䊧䊦䇸഍႐䈫䈚䈩䈱䉮䊮䊏䊠䊷䉺䇹䋩34䉮䊮䊏䊠䊷䉺䋽⸘▚䊜䊂䉞䉝(Computational Media)ౣ೑↪ᕈ䈏㜞䈇



ಣℂ䈪䈐䉎



⒖േᕈ䈏㜞䈇

䈇䉐䈇䉐䈭⴫⃻䈏น⢻䊡䊎䉨䉺䉴૕㛎䊜䊂䉞䉝(UEM)䈱⎇ⓥ
䋨ATR䌾㑆ἑ⎇䋩⸘▚䊜䊂䉞䉝䉕૕㛎䉕౒᦭䈜䉎䈢䉄䈱䊜䊂䉞䉝䈫䈚䈩૶䈍䈉䇸૕㛎䈮䉅䈫䈨䈒⍮⼂䇹䈱౒᦭䉕ഥ䈔䉎⸘▚䊜䊂䉞䉝 ૕㛎䈲䉣䊏䉸䊷䊄⸥ᙘ䈪䈅䉍䇮ⴕേ䈪䈅䉎 ૕㛎ⴕേ䈲䈇䈧䈪䉅䈬䈖䈪䉅⿠䈐䉎䈱䈪䊜䊂䉞䉝䈲ㆉ࿷䈜䉎5⴫⃻䊜䊂䉞䉝䈱ᱧผ䊡䊎䉨䉺䉴૕㛎䊜䊂䉞䉝(UEM)䈱ዷ㐿䋽૕㛎䊜䊂䉞䉝䈱ᱧผ

Original UEM: ATR䉡䉣䉝䊤䊑䊦 Visual UEM⸥ᙘ䈱ⷞⷡᡰេ䋨૕㛎䈱ⷞⷡ⊛౒᦭䋩⴩ⵝ䉮䊷䊂䉞䊈䊷䊃䋨⾼౉‛ຠ䈲૕㛎䈱ⷞⷡ⊛䈩䈏䈎䉍䋩ṽሼቇ⠌ with storytellingり૕⊛UEM䋨り૕䉮䊚䊠䊆䉬䊷䉲䊢䊮䈱౒᦭䇮વ㆐䋩䊨䊗䉾䊃ળ⼏䇮䉮䊚䊠䊆䊁䉞䋨ㅢା䈎䉌⸥㍳䇮⸥ᙘ䈻䋩

Classroom UEM႐䈮㑐䈜䉎UEM䋨႐䈱౒↪䋩uClassroom(ULAN)

Narrative UEM䊤䉴䉮䊷䈱ო↹ 䊌䊏䊦䉴 ⟠⊹⚕
 ᭉེ ශ೚ᛛⴚ ᤋ↹䊶౮⌀ 㔚ା䊶㔚⹤ 䊁䊧䊎䊶䊎䊂䉥 䉮䊮䊏䊠䊷䉺 䉟䊮䉺䊷䊈䉾䊃

Robotic (embodied䋩 UEM6䉅䈱䈏䈢䉍䈮䉋䉎UEM
78䉮䊚䊠䊆䉬䊷䉲䊢䊮䊜䊂䉞䉝䈱೑↪ᒻᘒ䈱ᄌㆫ䈎䉌⌑䉄䉎૕㛎web䉕ታ⃻䈜䉎䊡䊎䉨䉺䉴૕㛎䊜䊂䉞䉝䈱⎇ⓥ䊁䊷䊙

૕㛎W䌥䌢

䷲
丞两 䉻䉟䊋䉲䊁䉞 ⸒⺆⠡⸶ 䊜䊂䉞䉝䋨㕖⸒⺆䋩⠡⸶上 䊜䊂䉞䉝䷰ 䋨⇣ᢥൻ䇮⇣ಽ㊁䋩丶W䌥䌢઒ᗐ䷶ 䉮䊚䊠䊆䊁䉞 䊜䊷䊥䊮䉫䊥䉴䊃並 䊜䊂䉞䉝䌃䌓䌃䌗 䉮䊚䊠䊆䊁䉞丱ኻ 䊌䊷䉸䊅䊦 㔚ሶ䊜䊷䊦 㔚⹤ 䊁䊧䊎ળ⼏ 䍡䍸䍐䍖䍼䍚䍼䍛䍞䍻䍛⽎ 䊜䊂䉞䉝䊂䉞䉴䊒䊧䉟䶺 ၮᧄ䊜䊂䉞䉝 ⚕䊶䍺䍎䍪䍽䍹ᑪ▽䇮VR䉥䊷䊂䉞䉥᜛䶙㖸ᤋ௝䊁䉨䉴䊃႐䈱⴫⃻䷖䊡䊎䉨䉺䉴䊶䊈䉾䊃䊪䊷䉪䉟䊮䉺䊷䊈䉾䊃㔚᳇ㅢା䊜䊂䉞䉝䈱ᰴర㕖⸒⺆䋨䊜䊂䉞䉝䋩⠡⸶䈫૕㛎web䉕ታ⃻䈜䉎䊜䊂䉞䉝ᛛⴚ੖ᗵGoogle 㕖⸒⺆Ᏹ⼂䈱᭴▽ 䉦䊮䉇䉮䉿䋨ᥧ㤩⍮䋩䈱વ㆐ ૕㛎䈱⸥㍳䌾౒᦭䌾ഃ಴䊈䉾䊃䊪䊷䉪ᗵേ䈱౒᦭ lifelog910૕㛎W䌥䌢2.0૕㛎web –today-䉻䉟䊋䉲䊁䉞⸒⺆⠡⸶䊜䊂䉞䉝䋨㕖⸒⺆䋩⠡⸶䊜䊂䉞䉝䷲ 䋨⇣ᢥൻ䇮⇣ಽ㊁䋩
丞两
૕㛎W䌥䌢1.0上䷰丶W䌥䌢઒ᗐ䷶ 䉮䊚䊠䊆䊁䉞 䊜䊷䊥䊮䉫䊥䉴䊃䉮䊚䊠䊆䊁䉞並 䊜䊂䉞䉝䌃䌓䌃䌗丱ኻ 䊌䊷䉸䊅䊦 㔚ሶ䊜䊷䊦 㔚⹤ 䊁䊧䊎ળ⼏ 䍡䍸䍐䍖䍼䍚䍼䍛䍞䍻䍛⽎ 䊜䊂䉞䉝䊂䉞䉴䊒䊧䉟䶺 ၮᧄ䊜䊂䉞䉝 ⚕䊶䍺䍎䍪䍽䍹ᑪ▽䇮VR䉥䊷䊂䉞䉥᜛䶙㖸ᤋ௝䊁䉨䉴䊃႐䈱⴫⃻䷖SNS䋨blog䋩㸢 ૕㛎䈱䋨⸒⺆⊛䋩⸥㍳䈫౒᦭ 䊆䉮䊆䉮േ↹㸢 ૕㛎䈱䊎䊂䉥⴫⃻䈫ᗵേ䈱౒᦭ ੱജᬌ⚝䈲䈩䈭㸢 䉮䉿䊶⍮ᕺ䈱䋨⸒⺆⊛䋩౒᦭㓸ว⍮ ᄢⷙᮨⴕേ⸥㍳䈱⎇ⓥᄙᢙ㸢૕㛎web1.0

11䊜䊂䉞䉝䈱ᰴర䊡䊎䉨䉺䉴䊶䊈䉾䊃䊪䊷䉪䉟䊮䉺䊷䊈䉾䊃㔚᳇ㅢା䊈䉾䊃䊪䊷䉪12䋱䋰䋰ᐕ䈗䈫䈮ᣂ䈚䈇䉣䊮䉳䊮䈏⊒᣿䈘䉏䈩䈇䉎[⷏]䉟䊮䉺䊷䊋䊦䈱ᦼ㑆⫳᳇ᯏ㑐㩿㪪㫋㪼㪸㫄㩷㪜㫅㪾㫀㫅㪼㪀㩷㩷 㪈㪎㪍㪐㩷㪮㪸㫋㫋ౝΆᯏ㑐㩿㪞㪸㫊㫆㫃㫀㫅㪼㩷㪜㫅㪾㫀㫅㪼㪀㩷㩷㪈㪏㪎㪍 㪦㫋㫋㫆ᖱႎᯏ㑐㩿㪤㫀㪺㫉㫆㪧㫉㫆㪺㪼㫊㫊㫆㫉㪀㩷㩷㪈㪐㪎㪈㩷㪠㫅㫋㪼㫃ᣂ䈚䈇䉣䊮䉳䊮䈱ᵴ↪ᣇᴺ䈱⎇ⓥ㐿⊒໪⫥ ᵹㅢ ༵ᅢൻInformation Engineੱ㑆䈱⢻ജ䈱ടㅦེਇน⢻䉕น⢻䈮䈜䉎

UEM䋬䉟䊮䉺䊤䉪䊁䉞䊑䉝䊷䊃ᰴᦼ䉣䊮䉳䊮䈱⎇ⓥ

1314଀䋺䉟䊮䉺䊤䉪䊁䉞䊑䊶䉝䊷䊃⸘▚䊜䊂䉞䉝䈱ᣂ䈚䈇૶䈇ᣇ䈱ᮨ⚝ 䉟䊮䉴䉺䊧䊷䉲䊢䊮䈱ᄢ㊂↢↥䈱ᤨઍ ᗧ๧䊶ᕁ⠨䊶ᕁᗐ䉕વ䈋䉎 䉝䊷䊃䋧䉰䉟䉣䊮䉴㸢䉝䊷䊃䋧䉮䊮䊏䊠䊷䉺䊶䊁䉪䊉䊨䉳䊷䋧䉮䊮䊏䊠䊷䉺䊶䉰䉟䉣䊮䉴ᰴ䈱䉣䊮䉳䊮䈲䋿↢๮䋿⣖䋿⍮ⷡ䋿ᗵⷡ䋿ᤨ㑆䋿

1516䌈䌉䈱ၮ␆ℂ⺰ੱ㑆human䊍䊠䊷䊙䊮䉟䊮䉺䊐䉢䊷䉴humaninterfaceᖱႎᯏ᪾machineNorman䈱䋷Ბ㓏⹺⍮䊝䊂䊦Fitt’s Law઒ᗐ䉺䉴䉪ⓨ㑆17䊜䊮䉺䊦㗔ၞ

⋡ᮡ
goalታ
ⴕㆊ⒟

ᗧ ࿑
intention⹏ ଔ
evaluationᗧ๧〒㔌⸃ ㉼interpretationᠲ૞♽೉action specification
⴫⃻〒㔌

18

Norman䈱䋷Ბ㓏䊝䊂䊦⹏ଔㆊ⒟⹏ଔዤᐲ䋺 ⴫⃻〒㔌䈫ᗧ๧〒㔌〒㔌䈏ዊ䈘䈔䉏䈳⹺⍮⽶⩄䈏ዊ䈘䈒⦟䈇䉟䊮䉺䊐䉢䊷䉴଀䋺 䊘䉟䊮䉺䈱⒖േᚻᲑ䉦䊷䉸䊦䉨䊷 䊙䉡䉴 䉺䉾䉼䊌䊈䊦 䉳䉢䉴䉼䊞䊷
 㖸ჿ
 ᕁᔨ

ታ ⴕexecution⍮ ⷡ
perceptionᠲ૞⸒⺆ኻ⽎

⴫␜⸒⺆㆏ౕ䊶ᯏ᪾䊶ੱ㑆
physical system

Norman䈱䋷Ბ㓏䊝䊂䊦

1920䉟䊮䉺䊐䉢䊷䉴䈱䈠䈱ઁ䈱ℂ⺰䉁䈫䉄

Fitt㵭s Law
 䊡䊷䉱䊎䊥䊁䉞䉧䉟䊄䊤䉟䊮䊡䊎䉨䉺䉴૕㛎䊜䊂䉞䉝૕㛎䉕⸥㍳䊶౒᦭䈜䉎⸘▚䊜䊂䉞䉝 ૕㛎web䋨ᥧ㤩⍮䈱౒᦭䊶ᵹㅢ䋩 䉟䊮䉺䊤䉪䉲䊢䊮䉮䊷䊌䉴䋨㕖⸒⺆⍮⼂䋩

Nielsen, Norman䊝䊂䊦䊍䊠䊷䊙䊮䊒䊨䉶䉾䉰 䊡䊆䊋䊷䉰䊦䊂䉱䉟䊮 CSCW 䉺䊮䉳䊑䊦䉟䊮䉺䊐䉢䊷䉴 䈠䈱ઁታ〣䊂䊋䉟䉴䊶䉲䉴䊁䊛 ૕㛎⸥㍳䊶౒↪
 䊨䊗䉾䊃䈫䈱ㅪ៤2122䊜䊂䉞䉝ൻ䈜䈼䈐䊡䊷䉱䈱⁁ᴫ䊶ᢥ⣂䋽䉶䊮䉲䊮䉫䈚䈢䈇ኻ⽎り૕䊶ᐕ㦂䊶ᕈ᳁ฬ䊶᦯ⵝ䊶⡯ᬺ䊡䊷䉱⥄り䈱⁁ᴫ䉣䊷䉳䉢䊮䊃䈱⍮ⷡኻ⽎േ૞䊶⊒⹤⥝๧䊶ᗧ࿑䊶⸘↹ᖱേ䊶ᗵᖱ⍮⼂䊶ାᔨ䊡䊷䉱䈱⟎䈎䉏䈢⁁ᴫᤨೞ䊶႐ᚲઁ䈱ሽ࿷䊶⁁ᴫ䊶㑐ଥ੐⽎䊶ᄤ୥䊶੐ઙ

23

␠ળ䊶ᢥൻ

24

䊡䊷䉱⁁ᴫℂ⸃䈱䈢䉄䈱䉶䊮䉲䊮䉫䋨䋱䋩 䊷േ૞ℂ⸃䈱ო䊷䊡䊷䉱⁁ᴫℂ⸃䈱䈢䉄䈱ო

PUI䋨Perceptual User Interface) 䉳䉢䉴䉼䊞䊷⹺⼂ Human Reader䋨䋱䋹䋹䋰䋩 䊨䊗䉾䊃ળ⼏ᗵⷡ䉶䊮䉲䊮䉫䈱ო䊷േ૞䊶⊒⹤ ⋧੕૞↪䉶䊮䉲䊮䉫䈱ო ᖱേ䉶䊮䉲䊮䉫䈱ო䊷േ૞ ⥝๧䉶䊮䉲䊮䉫䈱ო䊷⋡✢ ૏⟎ᖱႎ䉶䊮䉲䊮䉫䈱ო25ኻ㕙䉮䊚䊠䊆䉬䊷䉲䊢䊮䈮䈍䈇䈩䉇䉍䈫䉍䈘䉏䉎ᖱႎ⸒⺆26⋧ᚻ䈮ਈ䈋䉎ශ⽎䈻䈱ฦⷐ⚛䈱ᓇ㗀䈱ഀว⸒⪲䈱ᗧ๧⸒⪲㆜䈇䊃䊷䊮䉝䉪䉶䊮䊃๟ㄝ⸒⺆ኻ㕙䉮䊚䊠䊆䉬䊷䉲䊢䊮䊥䉵䊛ᴉ㤩り૕⊛․ᓽ䊶᦯ⵝ⴫ᖱ㕖⸒⺆േ䈐䊶ᆫ൓⋡✢cf. 㕖⸒⺆䉮䊚䊠䊆䉬䊷䉲䊢䊮(䊙䉳䊢䊥䊷䊶F䊶䊐䉜䊷䉧䉴), ઁ〒㔌䊶⋧ኻ૏⟎27cf. Mehrabian, A28䊡䊷䉱⁁ᴫℂ⸃䋨䋲䋩䊷⋧੕૞↪䈱ო䊷䊨䊗䉾䊃䈱ᔕ↪

Ⓧᭂ⊛䈮௛䈐䈎䈔䉎 ႐䉕૞䉎䋨Ṷ಴䈜䉎䋩 ੱ䈫ⅣႺ䈱ਛ㑆䈮૏⟎䈜䉎 䉮䊚䊠䊆䉬䊷䉲䊢䊮䈚䈭䈏䉌តᩏ䈜䉎Ṷ಴੺⼔⍮⢒⹺⍮⑼ቇ

䊨䊗䉾䊃
29

䊡䊷䉱⁁ᴫℂ⸃䋨䋳䋩䊷ᖱേ䈱ო䊷䊡䊷䉱䈮ኒ⌕䈚䈩⴩ⵝ䋨Ᏹᤨ⌕↪䇮ਔᚻ䊐䊥䊷䋩30䉶䊮䉰䊷䊝䉳䊠䊷䊦⋧ኻ૏⟎䈱᷹ቯ਄ਅടㅦᐲ䉝䊅䊨䉫䊂䊋䉟䉴␠⵾ADXL202䊊䊈䉡䉢䊦␠⵾HMR3000⛘ኻ૏⟎⸘᷹䉡䉢䉝䊤䊑䊦䊶䉮䊮䊏䊠䊷䊁䉞䊮䉫೨ᓟടㅦᐲ䉲䊞䊷䊒␠⵾శ䉴䉟䉾䉼䈯䈇䈓䉎䉂䋨〒㔌䈱೙ᓮ䇮ᛴ䈋䉎䈭䈬䈱ធ⸅䉟䊮䉺䊤䉪䉲䊢䊮䋩䋲ゲടㅦᐲ⸘䋲ゲടㅦᐲ⸘䊃䉟䊶䉮䊮䊏䊠䊷䊁䉞䊮䉫31㔚ሶ䉮䊮䊌䉴㔚ሶ䉮䊮䊌䉴⿒ᄖ䊧䉲䊷䊋⿒ᄖ䊧䉲䊷䊋32䊡䊷䉱⁁ᴫ⹺⼂䋨䋴䋩䊷⥝๧䈱ო䊷䉴䊁䉾䊒䋨ᱠ⺞䋩ᬌ಴䈫䉴䊁䉾䊒⹺⼂
0.4x(k )z (k )

0.3
0.2

1.
2.
3.
4.

ടㅦ୯䈱䊏䊷䉪䉕․ᓽ㊂⋧㑐㑐ᢙ䈱ㆡ↪
ਥⷐ䈭䉴䊁䉾䊒䈱ᬌ಴ᱠ⺞๟ᦼ䈎䉌ᱠ᏷ផቯA c celeration (g)

0.1
0-0.1



-0.2

䊡䊎䉨䉺䉴䉶䊮䉰䊷䊦䊷䊛(USR)

-0.3



-0.4
-0.5

050

100150Tim e (s am ples )ⓨ㑆䈫䊡䊷䉱䈱ද⺞ⷞ✢⹺⼂ⵝ⟎

0.1
LevelUp
Down

0.08

Cros s-c orrelation func tion

1. 䉴䊁䉾䊒⒳೎: ᳓ᐔ䇮਄䇮ਅ
2. x, zടㅦᐲ䈱Kㄭற䈫⋧੕⋧㑐䈱⚵䉂ว䉒䈞
3. ⋧ኻ૏⟎⺋Ꮕ䈱ୃᱜ

0.06
0.04
0.02
0-0.02-0.04-0.06
-0.08
-0.1

䉡䉢䉝䊤䊑䊦䉶䊮䉰•䉦䊜䊤•䊙䉟䉪•⿒ᄖ✢ID䉶䊮䉰•↢૕䉶䊮䉰

05

10

15

20

25
lag

30

35

40

45

50

33

34

35

36

•䉦䊜䊤 ⅣႺ䉶䊮䉰•䊙䉟䉪•⿒ᄖ✢ID䉶䊮䉰•䋨䊝䊷䉲䊢䊮䉨䊞䊒䉼䊞䋩䊡䊷䉱⁁ᴫℂ⸃䋨䋵䋩䊷⢛᥊⍮⼂䈱ო䊷•Ᏹ䈮ነ䉍ᷝ䈉䉟䊮䉺䊐䉢䊷䉴䊶䉣䊷䉳䉢䊮䊃
•⥝๧䈫䉟䊮䉺䊤䉪䉲䊢䊮䈱䉶䊮䉲䊮䉫䌁䌉䌄䌅㪧㪸㫃㫄㪄㪞㫌㫀㪻㪼㪘㪾㪼㫅㫋㩷㪪㪸㫃㫆㫅㪚㪄㪤㪘㪧㪭㫀㫊㫋㪸㪄㫎㪸㫃㫂

AIDE

37

38

කᏧ䈫ᖚ⠪䈱䉮䊚䊠䊆䉬䊷䉲䊢䊮
䉩䊞䉾䊒

3940

૕㛎౒᦭䈻䈱䉝䊒䊨䊷䉼૕㛎౒᦭䋽౒᦭䈚䈢䈇૕㛎䉟䊔䊮䊃䋫䌕䌅䌍䋨䋽⸥㍳䊂䊋䉟䉴(capture, record)䋫⸥ㅀ䊶ⷐ⚂ (Interaction Corpus)䋫⴫␜䊶વ㆐ (Display)䋩

4142䌕䌅䌍ታ⃻䈻䈱䉝䊒䊨䊷䉼૕㛎ਥ૕䈫⸥㍳⠪䈱㑐ଥ䋨䋱䋩 ৻ੱ⒓⊛ⷞὐ⥄คવ⊛ᣣ⸥䋼䉡䉢䉝䊤䊑䊦䋾䋨䋲䋩 ਃੱ⒓⊛ⷞὐ䊧䊘䊷䉺䊷⊛⸥੐䋼ⅣႺ䉦䊜䊤䋬ઁ⠪䉡䉢䉝䊤䊑䊦䋾䋨䋳䋩 ੑੱ⒓⊛ⷞὐ䊌䊷䊃䊅䊷⊛ⷞὐ䋼䊨䊗䉾䊃䋬䈯䈇䈓䉎䉂䋾43Experiment
16 presenters
63 visitors
340GB
380,000 interactions
Nov. 2002
ATR Open House

44

Interaction Tracker and Tag(2002)
LED tagCapturing 䋨䉶䊮䉰䋫䉲䉴䊁䊛䋩

Micro computer㪣㪜㪛
CMOS camera for ID tracking

IR tracker

CCD camera for video recording46

45

⿒ᄖ䉺䉫䈮䉋䉎૏⟎䋫IDផቯ

47

Experiment
16 presenters
63 visitors
340GB
380,000 interactions
Nov. 2002
ATR Open House48

䉡䉢䉝䊤䊑䊦╙䋲਎ઍ䋨䋲䋰䋰䋳䋩

49

╙䋳਎ઍ
(࿯Ꮉ䈾䈎2005)

䋷䋵䌧50

หゲID䉦䊜䊤

䋱䋯䋵䉟䊮䉼 CMOS
䋱䋲䋶䌸䋹䋸↹⚛

䊖䉾䊃䊧䊮䉵

䋱䋯䋷䉟䊮䉼 CCD䋳䋲䋵䌸䋲䋴䋴↹⚛

䋲䋴䋵䋫
䋳䋸䋵䌧
51

52

ⷞ✢䈫㗡ᣇⷺ䈱Ꮕ(a) standing䋵䋰ᐲદ⮮䋨2005)

䋷䋰ᐲ53

శቇID䉺䉫䈱ᬌ಴ᕈ⢻

54శቇ䉺䉫䈏りㄭ䈮䉺䉫: 850nm IR LED2
 㻢0.0015 㱘W/cm /nmWii䊥䊝䉮䊮䉺䉫䊂䊷䉺䊧䊷䊃: 10 ms/bit 䊂䉮䊷䊄ㅦᐲ: min 300ms
 หᤨᬌ಴ᢙ: 20 ID ⒟ᐲ ⺋Ꮕ: 5cm ⒟ᐲ

Pixart␠CMOS䉟䊜䊷䉳䉶䊮䉰䉶䊮䉰䊷䊋䊷䈫䈇䈉ฬ䈱⿒ᄖ䉺䉫᳓ᐔ↹ⷺ90㫦ᤨ䇮3m 㔌䉏䈩

55

ID䈭䈚

LEDᾖ᣿

ㅊᓥㅦᐲ: 22 m/s 䋨᳓ᐔᣇะ䊶ℂ⺰୯䋩ታᤨ㑆䈱శὐ䊃䊤䉾䉨䊮䉫ⰯశἮ䋬੤ㅢ䉲䉫䊅䊦

56

䉟䊮䉺䊤䉪䉲䊢䊮䉮䊷䊌䉴⸥ㅀ䉟䊮䉺䊤䉪䉲䊢䊮䉮䊷䊌䉴ᄢⷙᮨ෼㓸䊂䊷䉺ੱ㑆ห჻䋬ੱ㑆䊷䊝䊉㑆䈱ᝄ䉎䉁䈇䊶ⴕേ ਄⸥䈮ᗧ๧⊛䈭䉝䊉䊁䊷䉲䊢䊮䉕ઃ䈔䈢䉅䈱 ᯏ᪾น⺒䈭䊙䊦䉼䊝䊷䉻䊦Ᏹ⼂⍮⼂


57

58

䉟䊮䉺䊤䉪䉲䊢䊮䉮䊷䊌䉴䈫⍮⼂䊔䊷䉴

⋡⊛
Human

䉟䊮䉺䊤䉪䉲䊢䊮䈱⹺⼂䊶วᚑ䈱䈢䉄䈱ㄉᦠ䋨c.f.
㖸ჿ⹺⼂䋬㖸ჿวᚑ䋩⹺⼂⁁ᴫ㸢䊤䊔䊦䋬ᗧ๧

Recognition䊤䊔䊦㸢੐଀䊔䊷䉴วᚑ䈖䈧ᥧ㤩⍮⠌ᘠ㖸ჿ䉮䊷䊌䉴

Interaction
CorpusSign Language DB䊝䊉䊝䊷䉻䊦วᚑ䊙䊦䉼䊝䊷䉻䊦Knowledge

Synthesis䉣䉨䉴䊌䊷䊃䉲䉴䊁䊛䉥䊮䊃䊨䉳䊷․ቯ㗔ၞ59ᯏ᪾⠡⸶䉮䊷䊌䉴

CYC䇮WordNet䇮EDR䇮GDAᏱ⼂60䉟䊮䉺䊤䉪䉲䊢䊮䊶䊌䉺䊷䊮䋨䊘䉴䉺䊷⺑᣿䉲䊷䊮䋺top-down䋩Interaction Composites Layer(multi-person interactions)
Jointattention

composites Layer

Look atan object

Look atan person

Is Captured at Talk-to

Gr.Discussion =(A “look at” B andB “look at” A andA “talk to” B andB “talk to” A)

Together with =(A “is captured at” S and
B “is captured at” S)

Primitives Layer

Segmentation Layer

SpeechIR tracker’s LED tagview61Speech

IR tracker’s LED tagview

An Application:
Video Summary(Sumi et.al.
Ubicomp2003)

62

Summary
video ofthe user’s
entire visit

List ofhighlighted
scenes during
the user’s visit䉝䊒䊥䉬䊷䉲䊢䊮䈫ታ㛎䊎䊂䉥

Annotations
for eachscene: time,
description,
durationVideo example ofconversation scene
63

OverheadcameraPartner’scamera

Selfcamera

64Video Summary (example)㸢૕㛎⸥㍳(lifelog)૕㛎౒᦭䉲䉴䊁䊛

65

66