Implementation of Dynamic Projection Mapping Framework based on Gesture Recognition for Stage Performance

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ⶊ╖

Ὃ㡆㦚 㥚䞲 㩲㓺㻮 㧎㔳 ₆⹮ ☯㩗 䝚⪲㩳㎮

ⱋ䞧

䝚

䝚⩞㧚㤢䋂

ῂ

ῂ䡚

*_{㍲㤎⹎❪㠊╖䞯㤦╖䞯ᾦ ⹎❪㠊Ὃ䞯ὒ,} +_ᾦ㔶㩖㧦

[email protected], [email protected], [email protected]

G

Implementation of Dynamic Projection Mapping

Framework based on Gesture Recognition

for Stage Performance

You-Jin Koh *_{, Tae-Won Kim}*_{, Yoo-Joo Choi}* *_{Dept. of Newmedia, Seoul Media Institute of Technology}

殚 檃檃 ⽎ ⏒ⶎ㠦㍲⓪ ⹎❪㠊㡗㌗㦚 ₆⹮䞲 ⶊ╖ Ὃ㡆㦮 ┺㟧䞲 ⹎❪㠊 䣾ὒ⯒ ⿚㍳䞮ἶ, ⶊ╖ Ὃ㡆㦚 㥚䞲 㩲㓺㻮 ₆⹮ ☯㩗 䝚⪲㩳㎮ ⱋ䞧 䝚⩞㧚㤢䋂⯒ ㍺Ἒ ῂ䡚䞲┺. 㧊⯒ 㥚䞮㡂, ☯㩗 䝚⪲㩳㎮ ⱋ 䞧 ₆⹮ ₆㫊 Ὃ㡆㠦㍲ Ὃ㡆㧦㦮 㩲㓺㻮㢖 㧊㠦 ➆⯎ ⹎❪㠊 䣾ὒ⯒ ⿚㍳䞮ἶ, ☯㩗 䝚⪲㩳㎮ ⱋ䞧 ₆㑶㦚 䣾㥾㩗㦒⪲ ῂ䡚䞮₆ 㥚䞮㡂 ⳾㎮ 䧞㓺䏶Ⰲ 㧊⹎㰖⯒ 㧊㣿䞲 CNN(Convolutional Neural Network) ₆⹮㦮 㩲㓺㻮 㧎㔳 ₆㑶㦚 ῂ䡚䞲┺. ⡦䞲, ῂ䡚♲ 㩲㓺㻮㧎㔳 ₆㑶㦚 ₆⹮㦒⪲ Ὃ㡆㧦㦮 ㍲⪲ ┺⯎ 㩲㓺㻮㢖 ⹎❪㠊 䣾ὒ⯒ ⰺ䃃㔲䌂 㑮 㧞⓪ 䝚⩞㧚 㤢䋂 ῂ䡚 ⌊㣿㦚 ㏢Ṳ䞲┺. 1. 昢嵦 ₆㫊㦮ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ Ὃ㡆㦖ٻ 㧊⹎ٻ Ⱒ✺㠊㰚ٻ ゚❪㡺㢖ٻὋ㡆ٻ㞞ⶊ㦮ٻ㕇䋂⯒ٻⰴ㿪㠊ٻ㔺㩲ٻὋ㡆ٻ➢⓪ٻ Ⱎ䂮ٻ ⱋ䞧ٻ ゚❪㡺Ṗٻ ㌂⧢㦮ٻ ☯㧧㠦ٻ 㔺㔲Ṛٻ ⹮㦧㦚ٻ 䞮⓪ٻ ộ㻮⩒ٻ⽊㧊Ợٻ䟞┺ډٻ 㾲⁒ٻ㩲㓺㻮ٻ 㧎㔳ٻ₆㑶㧊ٻ ⹲㩚䞮Ⳋ㍲ٻ㾲⁒㠦⓪ٻὋ㡆㧦㦮ٻ㩲㓺㻮㠦ٻ➆⧒ٻ㔺㔲Ṛٻ 㧎䎆⩟㎮ٻ 䗒䙂Ⲓ㓺Ṗٻ Ṗ⓻䞲ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ 㡆㿲㧊ٻ ὖ㕂㦚ٻ ⳾㦒ἶٻ 㧞┺ډٻ ╖┺㑮㦮ٻ ⹎❪㠊ٻ 㞚䔎ٻ 䗒䙂Ⲓ㓺Ṗٻ ⧒㧊ぢٻ Ὃ㡆㧎ٻ Ⱒ䋒ٻ Ὃ㡆㧦㦮ٻ ☯㧧㠦ٻ ➆⯎ٻ 䣾㥾㩗㧎ٻ ⹎❪㠊ٻ 㧊䗯䔎㠦ٻ ╖䞲ٻ 㻮Ⰲ㢖ٻ 㧊⯒ٻ ⽊┺ٻ 㣿㧊䞮Ợٻ 㫆㧧䞶ٻ 㑮ٻ 㧞⓪ٻ 䝚⩞㧚㤢䋂Ṗٻ 㣪ῂ♮ἶٻ㧞┺ډٻٻ ⽎ٻ⏒ⶎ㠦㍲⓪ٻ ╖䚲㩗㧎ٻ☯㩗ٻ䝚⪲㩳㎮ٻⱋ䞧ٻὋ㡆ٻ 㡆㿲ὒٻ 㩲㓺㻮ٻ 㧎㔳ٻ 㡆ῂٻ 䡚䢿㠦ٻ ╖䟊ٻ Ṛ┾䧞ٻ 㞢㞚⽊ἶٻ ⽊┺ٻ 䣾㥾㩗㧎ٻ 㩲㓺㻮ٻ 㧎㔳ٻ ῂ䡚㦚ٻ 㥚䟊ٻ ⳾㎮ٻ 䧞㓺䏶Ⰲٻ 㧊⹎㰖⯒ٻ 㧊㣿䞲ٻ ڞککڃڞۊۉۑۊۇېۏۄۊۉڼۇٻ کۀېۍڼۇٻکۀۏےۊۍۆڄ₆⹮㦮ٻ㩲㓺㻮ٻ㧎㔳ٻ㔺䠮㦚ٻ㰚䟟䞮ἶڇٻ 㩲㓺㻮ٻ 㧎㔳㦚ٻ ₆⹮䞲ٻ ⶊ╖ٻ Ὃ㡆㠦ٻ 㩗䞿䞲ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻⱋ䞧ٻ䝚⩞㧚㤢䋂⯒ٻ㍺Ἒٻῂ䡚䞲┺ډٻ 2. 稊嵢洣晞 廻穗 匶愞 惾娚檺 橊瞾 碂磲彂枪歆 洢枪熞 汾柣匶朦 笊筯 2.1 惾娚檺 橊瞾 碂磲彂枪歆 壟洇 稊嵢洣晞 廻穗 䝚⪲㩳㎮ٻⱋ䞧㦖ٻ䒂㌂䞮⓪ٻ╖㌗ⶒ㦮ٻ䘟Ⳋ㠦ٻṖ㌗㦮ٻ ⶊ╖ٻὋṚ㦚ٻ㺓㫆䞶ٻ㑮ٻ㧞₆ٻ➢ⶎ㠦ٻザ⯎ٻⶊ╖ٻ㧻Ⳋٻ 㩚䢮㦚ٻ 䐋䞲ٻ 㧊㟒₆ٻ 㩚ṲṖٻ Ṗ⓻䞮┺ډٻ ڃ⁎Ⱂٻ ڌڄ㦖ٻ Ὃ㡆㧦⯒ٻ ₆㭖㦒⪲ٻ Ṗ㌗㦮ٻ ڎڟ ⺆ἓ㦚ٻ 㧛䡖ٻ Ὃ㡆㧦Ṗٻ Ⱎ䂮ٻ 㔺㩲㢖ٻṯ㦖ٻ 䣾ὒ⯒ٻ 㭖┺ډٻ㡂₆㠦ٻ 㩲㓺㻮ٻ 㧎㔳ٻ ₆㑶㧊ٻ ▪䟊㰚ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻ ⱋ䞧㦖ٻ Ὃ㡆㧦Ṗٻ ⶊ╖ٻ 㥚㠦㍲ٻ㧦㔶㦮ٻⴎ㰩Ⱒ㦒⪲ٻⲪ㔲㰖ٻ㩚╂㦚ٻ䞶ٻ㑮ٻ㧞Ợٻ 䞲┺ډٻ ڃ⁎Ⱂٻ ڍڄٻ ṯ㧊ٻ 㩲㓺㻮ٻ 㧎㔳ὒٻ 㧎䎆⩟㎮㧊ٻ Ṗ⹎♲ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ ₆㑶㦖ٻ 㡞㑶Ṗ㢖ٻ ὖ⧢ṳ㧊ٻ ṯ㦖ٻὋ㡆ٻ㞞㠦㍲ٻ䞾℮ٻ㯦₎ٻ㑮ٻ㧞☚⪳ٻⰢ✶┺ډٻ ڃ⁎Ⱂٻڌڇڍڄٻ䝚⪲㩳㎮ٻⱋ䞧ٻ䗒䙂Ⲓ㓺ٻ㡞㔲 ڌڇڍڶڍڈڎڸڇٻٻ 2.2 娫峲埣 匶愞汞 洢枪熞 汾柣 㾲⁒ٻ ❻⩂┳㦚ٻ ₆⹮䞲ٻ 㩲㓺㻮ٻ 㧎㔳ٻ ⹿⻫㧊ٻ ⏨㦖ٻ ㎇⓻㦚ٻ ⽊㧊ἶٻ 㧞┺ډٻ 㩲㓺㻮ٻ ⹥ٻ ☯㧧ٻ 㧎㔳㦚ٻ 㥚䞲ٻ ❻⩂┳ٻ 㩧⁒⻫㦖ٻ ڃ⁎Ⱂٻ ڏڄ㢖ٻ ṯ㧊ٻ 䋂Ợٻ ㎎ٻ Ṗ㰖⪲ٻ ⋮⒲┺ډٻ 䞮⋮⓪ٻ 䞯㔋㠦ٻ ㌂㣿䞮⓪ٻ 㔶ἓⰳ㦮ٻ ἶ☚䢪㢖ٻ 㧛⩻◆㧊䎆㦮ٻ 㩚㻮Ⰲٻ ⁎Ⰲἶٻ ڭککڃڭۀھېۍۍۀۉۏٻ کۀېۍڼۇٻ کۀۏےۊۍۆڄὒٻ ṯ㧊ٻ 㡆㏣ٻ ◆㧊䎆ڃڮۀیېۀۉھۀٻ ڟڼۏڼڄ⯒ٻ 㧊㣿䞲ٻ 㔲Ṛ㩗ٻ ⹿⻫✺ڃۏۀۈۋۊۍڼۇٻ ۈۀۏۃۊڿێڄٻ ✺㧊ٻ 㧞┺ڶڎڸډٻ ⽎ٻ ⏒ⶎ㠦㍲⓪ٻ ◆㧊䎆㦮ٻ ㌂㣿⨟㦚ٻ 㭚㡂ٻ ㎇⓻㦚ٻ ⏨㧊⓪ٻ ⳾㎮₆⹮ٻ 㧛⩻ٻ 䔏㰫Ṩ㦚ٻ 䢲㣿䞮⓪ٻ ⹿⻫㦚ٻ 䌳䞮㡂ٻ ⳾㎮ٻ 䧞㓺䏶Ⰲٻ 㧊⹎㰖⯒ٻ 䞯㔋ٻ ◆㧊䎆⪲ٻ ㌂㣿䞮⓪ٻ ڞککٻ ₆⹮㦮ٻ 㩲㓺㻮ٻ 㧎㔳ٻ ⹿⻫㦚ٻ ῂ䡚䞮ἶٻ 㧊⯒ٻ㌂㣿䞮㡖┺ډٻ 3. 割笊 愕 柪竞 3.1 割笊 洢枪熞 ڗ䚲ٻ ڌڙ㦖ٻ 㰗ὖ㩗ٻ 㩲㓺㻮ٻ ತ₆⳾㦒₆ಥڇٻ ತ㧻䛣ٻ 㘮₆ಥڇٻ ತ⹲㹾₆ಥ⪲ڇٻ ⽎ٻ ⏒ⶎ㠦㍲⓪ٻ 䟊╏ٻ 㩲㓺㻮✺㦚ٻ 㧎㔳䞮ἶٻ ṗٻ 㩲㓺㻮㠦ٻ 䟊╏䞮⓪ٻ

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㧎䎆⩟㎮㦚ٻῂ䡚䞲┺ډٻ ٻ ڗ䚲ٻڌڙٻῂ䡚ٻ㩲㓺㻮ٻ㫛⮮ٻ ₆⳾㦒₆ٻ 㧻䛣ٻ㘮₆ٻ ⹲㹾₆ٻ ٻ ٻ ٻ ٻ 3.2 微微晞 粎枪皦庲 決惾滆 匶愞 洢枪熞 汾柣 ⽎ٻ ⏒ⶎ㠦㍲⓪ٻ 㩲㓺㻮ٻ 㧎㔳ٻ 㔺䠮㠦ٻ ╖䞲ٻ 㧛⩻◆㧊䎆⪲ٻڨۊۏۄۊۉٻڣۄێۏۊۍ۔ٻڤۈڼۂۀڃڨڣڤڄ⯒ٻ㌂㣿䞲┺ډٻ ڨڣڤ ⓪ٻ ☯㧧㧊⋮ٻ 㩲㓺㻮㦮ٻ 㰚䟟ٻ ἓ⪲⯒ٻ 㧊䟊䞶ٻ 㑮ٻ 㧞⓪ٻ 㩫㩗ٻ 㧊⹎㰖ٻ 䎲䝢Ⱅ㦒⪲ڇٻ 㡂⩂ٻ 䝚⩞㧚㦒⪲ٻ ⋮⒮⓪ٻ 䞮⋮㦮ٻ ☯㧧ٻ ◆㧊䎆⯒ٻ 㩗㦖ٻ Ⲫ⳾Ⰲ⪲ٻ 䢲㣿䞶ٻ 㑮ٻ㧞┺ڶڏڸډٻ ٻ 3.3 洢枪熞 懊 痆冥 欇旇 箮刂 ڗ䚲ٻ ڍڙ⓪ٻ 㩲㓺㻮㢖ٻ ⰺ䃃♮⓪ٻ 㧎䎆⧯㎮ٻ 䣾ὒ⯒ٻ ⋮䌖⌊ἶٻ 㧞┺ډٻ ڗ䚲 ڑڙ㦮ತⰢ㎎ಥٻ 㩲㓺㻮㦮ٻ ἓ㤆ڇٻ ㌂㣿㧦⯒ٻ㧎㔳䞮㡂ٻ䝚⪲⁎⧾ٻ㔲㧧㦚ٻ䕦┾䞮⓪ٻ㻯☚⪲ٻ ㌂㣿♲┺ډٻ ತ₆⳾㦒₆ಥٻ 㩲㓺㻮⓪ٻ 㭒⼖㠦ٻ ⹲㌆䞮▮ٻ ケ✺㧊ٻ ㌂㣿㧦㦮ٻ 㭧㕂㦒⪲ٻ ⳾㡂ٻ ⶟㼦㰖⓪ٻ 䣾ὒ⯒ٻ 㭖┺ډٻ ತ㧻䛣ٻ 㘮₆ಥ⓪ٻ Ὃ㡆㧦㦮ٻ ⚦ٻ ㏦ٻ 㭧㕂㠦㍲ٻ ㏦㦚ٻ ㄭ⓪ٻ ⹿䟻㦒⪲ٻ 䕢䕆䋊ٻ ▿㠊ⰂṖٻ ⹲㌂♲┺ډٻ ತ⹲㹾₆ಥ⓪ٻ 㧻䛣㘮₆㢖ٻ ṯ㦖ٻ 䣾ὒ⪲ٻ 㡆ἆ♮ἶڇٻ 㧻䛣㘮₆ڊ⹲㹾₆㦮ٻ Ⱎ㰖Ⱏٻ 㔲㩦㠦ٻ ⿞↙ٻ 䡫䌲㦮ٻ 䕢䕆䋊㧊ٻ㭒⼖㦒⪲ٻ⹲㌆䞮㡂ٻ䙃⹲䣾ὒ⯒ٻ䚲䡚䞲┺ډٻ ڗ䚲ٻڍڙٻṗٻῂ䡚ٻ㩲㓺㻮㠦ٻ╖䞲ٻ㧎䎆⩟㎮ٻ䣾ὒٻ ㌂㣿㧦ٻ㧎㔳ٻٻ ₆⳾㦒₆ٻ 䣾ὒٻ 㧻䛣㘮₆ٻ ڊ⹲㹾₆ٻ䣾ὒٻ 䙃⹲ٻ䣾ὒٻ ٻ ٻ 3.4 洢枪熞歆 惾娚檺 箮刂汞 廪獳 洛汞 㩲㓺㻮㢖ٻ ⰺ䃃♮⓪ٻ ⹎❪㠊ٻ 䣾ὒ⓪ٻ 䎣㓺䔎⪲ٻ ῂ㎇♮⓪ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ ῂ㎇ٻ 䕢㧒㠦ٻ 㩫㦮䞲┺ډٻ ڗ䚲 ڎڙ㦖ٻ ῂ㎇䕢㧒㠦㍲ٻ 㩲㓺㻮㢖ٻ ⰺ䃃ٻ 䣾ὒ⯒ٻ 㩫㦮䞮⓪ٻ′䂯ὒٻ㧊㠦ٻ➆⧒ٻ㩫㦮䞲ٻ䡫㔳㦚ٻ⽊㡂㭖┺ډٻ ڗ䚲ٻڎڙٻ㩲㓺㻮㢖ٻ⹎❪㠊ٻ䣾ὒٻⰺ䃃㦚ٻ㥚䞲ٻῂ㎇ٻ䕢㧒ٻ′䂯ٻ 㩲㓺㻮/⹎❪㠊 䣾ὒ 㩫㦮 ′䂯 㦮⹎ Num_Gesture: 3 䌖ỵ 㩲㓺㻮 㑮 GestureDir:“gesture dir ⳛ” 䞯㔋㢚⬢ ⺆䙂◆㧊䎆❪⩟䏶Ⰲⳛ Num_Effect:4 ⹎❪㠊 䣾ὒ 㑮 Effect1:“ParticleEffect1” 䕢䕆䋊 䣾ὒ⻞䢎 Effect2: “ParticleEffect2” 䕢䕆䋊 䣾ὒ⻞䢎 Effect3: “ParticleEffect3” 䕢䕆䋊 䣾ὒ⻞䢎 Effect4: “ParticleEffect4” 䕢䕆䋊 䣾ὒ⻞䢎 Performer check 1: 1 Performer Ṗ 㧞┺ἶ

䕦┾♮⓪ 1 㦮 ἓ㤆, 1 ⻞㧊䗯䔎 ⰺ䃃 Gesture2: 2 Gesture2 ὒ 2 ⻞㧊䗯䔎 ⰺ䃃 Gesture3: 3 Gesture3 ὒ 3 ⻞㧊䗯䔎 ⰺ䃃 Gesture3: 4 Gesture4 ὒ 4 ⻞㧊䗯䔎 ⰺ䃃 ٻ 3.5 柪竞 愯憛 㽳ٻڐ ⳛ㦮ٻ㺎Ṗ㧦Ṗٻ䞲ٻ☯㧧Ⱎ┺ ڌڋ 䣢㝿ٻ⹮⽋䞲ٻ䤚ٻ ṗٻ 㡗㌗㦚ٻ 䝚⩞㧚⼚⪲ٻ 㴒Ṳ㠊ٻ 㧊⹎㰖ٻ ◆㧊䎆⯒ٻ ㌳㎇䞮㡖┺ډٻڏ ⳛ㦮ٻ◆㧊䎆⯒ٻ䞯㔋◆㧊䎆⪲ٻ㌂㣿䞮ἶٻ ڌ ⳛ㦮ٻ ◆㧊䎆⓪ٻ 䎢㓺䔎ٻ ◆㧊䎆⪲ٻ ㌂㣿䞮㡖┺ډٻ 㾲㫛ٻ ㌳㎇♲ٻ ◆㧊䎆㎡㠦ٻ ╖䟊ٻ ڞکک 㦚ٻ 䢲㣿䞮㡂ٻ 䦧⺇ٻ 㡗㌗㧎ٻ ⳾㎮ٻ 䧞㓺䏶Ⰲٻ 㧊⹎㰖ٻ ₆⹮㦮ٻ 㩲㓺㻮ٻ 㧎㔳ٻ 㔺䠮㦚ٻ 㰚䟟䞮㡖┺ډٻ ڗ䚲ٻ ڏڙ⓪ٻ ڗ䚲ٻ ڌڙ㦮ٻ 㩲㓺㻮㠦ٻ ὖ䞲ٻڨڣڤ 㧊┺ډٻٻ ٻ ڗ䚲ٻڏڙٻṗٻ䌖ỵٻ㩲㓺㻮㠦ٻ╖䞲ٻ⳾㎮ٻ䧞㓺䏶Ⰲٻ㧊⹎㰖ٻ ₆⳾㦒₆ 㧻䛣 㘮₆ ⹲㹾₆ ٻ 3.6 柪竞 冶刂 ڗ䚲ٻ ڐڙ⓪ٻ ṗٻ 㩲㓺㻮㠦ٻ ╖䞲ٻ 㧎㔳ٻ 㔺䠮㦚ٻ 㰚䟟䞲ٻ ἆὒ㧊┺ډٻٻ ٻ ڗ䚲ٻڐڙٻ⳾㎮ٻ䧞㓺䏶Ⰲٻ㧊⹎㰖ٻ㧛⩻㠦ٻ➆⯎ٻ㩲㓺㻮ٻ㧎㔳⮶ٻ ⹥ٻ䞮⋮㦮ٻ㩲㓺㻮ٻ㧎㔳㠦ٻỎⰂ⓪ٻ㔲Ṛٻ Number of filters in Convolutio n Layer1 Number of filters in Convolutio n Layer2 Number of nodes in FC layer Accuracy 32 32 32 0.90 16 16 16 0.95 8 8 8 0.91 ٻ ڗ䚲ٻ ڑڙ㦖ٻ 㾲㫛㩗㦒⪲ٻ ῂ䡚♲ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ 㞶䝢Ⰲ䅖㧊㎮㦚ٻ㌂㣿䞮㡂ٻ㔺㩲⪲ٻ㩲㓺㻮⯒ٻ䀾䟞㦚ٻ➢ٻ ⽊㡂㰖⓪ٻ㧎䎆⩟㎮ٻⱋ䞧ٻ䣾ὒ㧊┺ډٻἆὒ㧊┺. G ڗ䚲ٻڑڙٻṗٻ㩲㓺㻮㠦ٻ╖䟊ٻῂ䡚♲ٻⱋ䞧ٻ䣾ὒٻ ㌂㣿㧦ٻ㧎㔳ٻٻ ₆⳾㦒₆ٻ 䣾ὒٻ 㧻䛣ٻ㘮₆ٻ 䣾ὒٻ ⹲㹾₆ٻ䣾ὒٻ ٻ ٻ 4. 冶嵦 㤆Ⰲ⓪ٻ ₆㫊㦮ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ Ὃ㡆ٻ ₆㑶㦮ٻ 㥶㡆䞲ٻ Ὃ㡆ٻ 㡆㿲㦚ٻ 㥚䟊ٻ ڨڣڤٻ ₆⹮㦮ٻ 㩲㓺㻮ٻ 㧎㔳ٻ ⹿⻫㦚ٻ 䐋䞲ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ 䝚⩞㧚㤢䋂ٻ ῂ䡚㦚ٻ 㔲☚䞮㡖┺ډٻ 䟊╏ٻ ⏒ⶎ㠦㍲ٻ 㩲㞞♲ٻ ⹿⻫㦖ٻ ڨڣڤ ⧒⓪ٻ ⽊┺ٻ Ṗ⼒㤊ٻ Ⲫ⳾Ⰲ⯒ٻ 䐋䟊ٻ 㩲㓺㻮⯒ٻ 㧎㔳䞮ἶٻ 㞚㤙䛡㦚ٻ 㨂䡚䞲┺ډٻ ⽎ٻ ⏒ⶎ㠦㍲ٻ ῂ䡚䞲ٻ ☯㩗ٻ 䝚⪲㩳㎮ٻ ⱋ䞧ٻ 䝚⩞㧚㤢䋂⓪ٻ ☯㩗ٻ 䝚⪲㩳㎮㠦ٻ ╖䟊ٻ ㌂㣿㧦㦮ٻ ἓ䠮㦚ٻ ⽊┺ٻ 㓓Ợٻ 㥶☚䞶ٻ 㑮ٻ 㧞ἶٻ 㡆㿲䞮ἶ㧦ٻ 䞮⓪ٻ ⱋ䞧ٻ 㡆㿲㦮ٻ ザ⯎ٻ 䎢㓺䔎Ṗٻ Ṗ⓻䞶ٻ ộ㦒⪲ٻ㡞㌗♲┺ډٻ ٻ 斲斲汞 匆 㧊ٻ 㡆ῂ⓪ٻ ದ䞲ῃ㡆ῂ㨂┾ٻ 㧊Ὃ䞯Ṳ㧎₆㽞㡆ῂ㰖㤦㌂㠛ٻ ڃکڭڡڈ ڍڋڌڒڭڌڟڌڜڌڝڋڎڋڎڐڒڌړڄಧ㦮ٻ㰖㤦㦚ٻ⹱㞚㍲ٻ㑮䟟♮㠞┺ډٻ 焾処怾竒

[1] The Most Amazing Multimedia Act Gets A Simo Cowell Standing Ovation!-America’s Got Talent 2018, https://youtu.be/B3ZlW4_-BI4

[2] Multimedia Show / video mapping 360 / dome projection / Danel Stryjecki, https://youtu.be/zrF52zwk284

[3] Mayam Asadi-Aghbolaghi, Albert Clapes, Marco Bellantonio. A survey on deep learning based approaches for action and gesture recognition in image sequences. Washington, D.C., USA IEEE 2017

[4] Motion History Images from Wikipedia, https://en.wikipedia.org/wiki/Motion_History_Images

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