ARG WI2 No.3, 2013 Kinect ʹΑΓ؍ଌ͞Εͨਓͷಈ࡞Λઆ໌͢Δ֬తޠݴੜͷ औΓΈ খྛ ਸ਼† ق, a খྛ Ұ †, b ຑੜ ӳथ ††, c † ͓ͷਫঁࢠେֶେֶӃ ਓؒจԽՊֶڀݚՊ ཧֶઐ߈ ใՊֶίʔε †† ࢈ٕۀज़૯߹ ॴڀݚೳγεςϜڀݚ෦ a) [email protected] b) [email protected] c) [email protected] ֓ཁ ηϯαͳͲʹΑͬͯ؍ଌ͞ΕΔใͷຆͲ࣌ྻܥσʔλͰ͋ΓɼϏοάσʔλΛѻ͏࣌ʹ͓͍ͯɼ؍ ଌ͞Εͨ࣌ྻܥσʔλͷத͔Β༗ӹͳใΛऔಘ͠ɼͦͷ༰Λཧղ͢Δख๏ͷ։ൃ͕ॏཁͱͳΔɽ࣌ྻܥσʔ λͷੳํ๏ʹɼτϨϯυͷ༧ଌෳσʔλؒͷ૬ؔؔͷੳͳͲ༷ʑͳํ๏͕ଘࡏ͢ΔɽҰํͰɼ࣌ܥ ྻσʔλͷ༰Λཧղ͢ΔʹՄࢹԽͳͲͷख๏͕༻͍ΒΕ͍ͯΔɽ͔͠͠ɼϩϘοτͳͲෳͷηϯαʹΑͬ ͯऔಘ͞Εͨ࣌ྻܥσʔλͷใʹ͖ͮجঢ়گΛೝࣝ͢Δඞཁ͕͋Δ߹ɼऔಘ͞ΕͨใΛΑΓநͷߴ͍ ϨϕϧͰ؍ଌ͞ΕͨσʔλΛද͢ݱΔඞཁ͕͋Δɽͦͷ͜ͱʹண͠ɼզʑ؍ଌ͞Εͨ࣌ྻܥσʔλͷৼΔ ͍ΛͰޠݴઆ໌͢Δख๏ͷ։ൃΛࢦ͠ɼͦͷҰͭͱͯ͠ɼKinect ͔ΒಘΒΕͨಈը૾ͷใΛೖྗͱͨ֬͠ తͳςΩετੜख๏ΛఏҊ͢Δɽ Ωʔϫʔυ Kinectɼ࣌ྻܥσʔλɼSAXɼରઢܗϞσϧɼόΠάϥϜϞσϧɼಈతܭը๏ 1 ͡Ίʹ ࡞Λઆ໌͢ΔςΩετੜͱͯ͠ɼRegneri Β [2] ௐ ηϯαͳͲʹΑͬͯ؍ଌ͞ΕΔใͷຆͲ࣌ྻܥ ཧΛߦ͍ͬͯΔಈը૾͔ΒɼඃࣸମͷߦಈΛઆ໌͢Δς σʔλͰ͋ΓɼϏοάσʔλΛѻ͏࣌ʹ͓͍ͯɼ؍ ΩετੜΛߦ͍ͬͯΔɽ൴Β Yu Βͱಉ༷ʹਓͷಈ ଌ͞Εͨ࣌ྻܥσʔλͷத͔Β༗ӹͳใΛऔಘ͠ɼͦ ࡞ͱͦΕΛઆ໌͢ΔจষͷϖΞ͔Βಈ࡞ʹରͯ͠దͳ ͷ༰Λཧղ͢Δख๏ͷ։ൃ͕ॏཁͱͳΔɽ࣌ྻܥσʔ දݱΛ͍ͯ͠ূݕΔɽUshiku Β [3] ɼ੩ࢭըͱͦΕΛ λͷੳํ๏ʹɼτϨϯυͷ༧ଌෳσʔλؒͷ૬ આ໌͢ΔΩϟϓγϣϯͷϖΞΛֶश͠ɼྨࣅͨ͠ը૾ʹ ؔؔͷੳͳͲ༷ʑͳํ๏͕ଘࡏ͢ΔɽҰํͰɼ࣌ܥ ྨࣅͨ͠ΩϟϓγϣϯΛੜ͢Δख๏ΛఏҊ͍ͯ͠Δɽ ྻσʔλͷ༰Λཧղ͢ΔʹՄࢹԽͳͲͷख๏͕༻͍ ·ͨɼಈը૾ͷޠݴԽʹ͓͍ͯɼTakano Β [4, 5] ɼҰ ΒΕ͍ͯΔɽ͔͠͠ɼϩϘοτͳͲෳͷηϯαʹΑͬ ࿈ͷਓͷߦಈΛӡಈ߸هͷ n-gram ͱͯ͠ද͠ݱɼӡಈ ͯऔಘ͞Εͨ࣌ྻܥσʔλͷใʹ͖ͮجঢ়گΛೝࣝ͢ ݺͱ߸هΕΔਓͷಈ࡞Λࣔͨ͠ҙຯϥϕϧ͔Β୯ޠͷ Δඞཁ͕͋Δ߹ɼऔಘ͞ΕͨใΛΑΓநͷߴ͍ ࿈ߏΛදͨ͠ݱϞσϧΛ௨ͯ͡୯ޠͷฒͼΛ࡞Δจ ϨϕϧͰ؍ଌ͞ΕͨσʔλΛද͢ݱΔඞཁ͕͋Δɽͦͷ ੜख๏ΛఏҊ͍ͯ͠Δɽ ͜ͱʹண͠ɼզʑ؍ଌ͞Εͨ࣌ྻܥσʔλͷৼΔ ·ͨɼLiang Β [6] ɼςΩετͱҙຯͱͷؔΛֶ ͍ΛͰޠݴઆ໌͢Δख๏ͷ։ൃΛࢦ͠ɼͦͷҰͭͱ͠ श͢Δख๏ΛఏҊ͓ͯ͠Γɼͦ͜ͰɼΠϕϯτσʔ ͯɼKinect ͔ΒಘΒΕͨಈը૾ͷใΛೖྗͱͨ֬͠ λϕʔεͷϨίʔυͰදͤΔͱԾఆ͠ɼϨίʔυͱࣗવ తͳςΩετੜख๏ΛఏҊ͢Δɽ Ͱޠݴද͞هΕͨઆ໌จͱͷؔ࿈ΛػցֶशʹΑͬͯऔ ಘ͍ͯ͠ΔɽAngeli Β [7] ɼ Liang Β [6] ͕ఏҊͨ͠ 2 ؔ࿈ڀݚ Ϟσϧʹͮ͘جજࡏใͱදใΛςΩετੜ͢Δ ۙɼϚϧνϞʔμϧใΛޠݴใͰද͕͢ڀݚ ख๏ΛఏҊ͍ͯ͠Δɽ·ͨɼKonstas Β [8, 9] ɼೖྗ Μʹ͞ڀݚΕ͖͍ͯͯΔɽ2013 ͷࣗવॲޠݴཧ ใݻ༗ͷߏΛઆ໌͢Δ֬తͳࣗ༝จ຺จ๏Λఆٛ Ͱͷ࠷ߴๆͱ͞ΕΔࠃࡍձٞ ACL ʹ͓͚Δ࠷༏लจ ͓ͯ͠ΓɼLiang Β [6] Angeli Β [7] ͱಉ༷ʹɼσʔ ʹɼYu Β [1] ʹΑΔಈըʹөΔਓͱͱͷ૬༻࡞ޓ λϕʔεͷϨίʔυͱઆ໌จΛ༻͍͍ͯΔɽ൴Βɼॏ Λઆ໌͢ΔςΩετੜ͕ڀݚબΕͨɽ൴ΒͷͰڀݚ ΈΛՃ͑ͨάϥϑʹΑͬͯจ๏Λද͠ݱɼ༩͑ΒΕͨೖ ɼମಈ࡞ͷೝࣝͷํ๏ͱͯ͠ɼମಈ࡞ΛҰͭͷ࣌ ྗʹରͬ͠ͱదͳಋग़Λ͚ͭݟΔ͜ͱͰςΩε ྻܥσʔλͱͯ͠ද͠ɼӅΕϚϧίϑϞσϧΛ༻͍ͯͦ τੜΛߦ͍ͬͯΔɽ ͷಈ࡞ϞσϧΛֶशɾೝࣝ͠ɼޠݴΛද͢ҙຯϥϕϧΛ ຊͰڀݚɼLiang Β [6] ͷख๏Λࢀߟʹͯ͠ɼࢹ֮ ༩͢Δ͜ͱʹΑΓޠݴԽΛߦ͍ͬͯΔɽ·ͨɼਓͷಈ ใͱͯ͠औಘ͞ΕΔਓͱମͷৼΔ͍Λද࣌͢ྻܥ σʔλͱಈ࡞Λදࣗ͢વޠݴͷઆ໌จͱͷରԠΛରઢ Copyright is held by the author(s). The article has been published without reviewing. ܗϞσϧΛ༻ֶ͍ͯश͠ɼಈ࡞ͷҙຯΛද͢தؒදݱΛ Web ΠϯςϦδΣϯεͱΠϯλϥΫγϣϯڀݚձ༧ߘू ਤ 1 ಈը૾Λೖྗͱ͢Δ֬తςΩετੜͷΈ ผ͢Δɽதؒද༻ʹͱ͝ݱҙ͞ΕͨόΠάϥϜωοτ ࠲ඪͷ࣌ྻܥσʔλΛऔಘ͢Δ (ਤ 2 ࢀর)ɽ·ͨɼମ ϫʔΫΛ༻͍Δ͜ͱʹΑΓɼͦͷಈ࡞ͷҙຯΛද͢ݱΔ ͷಈ࡞ͷ࣌ྻܥσʔλɼύʔςΟΫϧϑΟϧλʢ3.1.1 Β͍͠จΛੜ͢ΔɽఏҊ͢ΔςΩετੜख๏ʹ ʹৄઆʣΛ༻͍Δ͜ͱͰऔಘ͢Δɽ ɼจ๏Λඞཁͱ͢ΔΑ͏ͳෳࡶͳจੜ͢Δ͜ͱ͕ Ͱ͖ͳ͍͕ɼಈը૾Λೖྗͱ͠ɼ͕ߴ͍දߏͰݱ ͞ΕΔจΛ༰қʹੜ͢Δ͜ͱ͕ՄೳͰ͋Δɽ ࢹ֮ใͷޠݴԽͷΈ 3 ຊڀݚͷ֓ཁΛਤ 1 ʹࣔ͢. ·ͣɼKinect1 ͕ͭਓ ͷࠎ֨Λ͢ΔϥΠϒϥϦͱύʔςΟΫϧϑΟϧλΛ ༻͍Δ͜ͱͰɼਓͱͷಈ͖Λ࣌ྻܥσʔλͱͯ͠औಘ ͢Δɽऔಘ͞Εͨ࣌ྻܥσʔλ͍͔ͭ͘ͷ࣍ݩѹॖ࡞ ۀΛߦ͍ɼσʔλͱࣗવޠݴͷཱͪΛ͢Δதؒදͱݱ ͱʹσʔλϕʔεʹ֨ೲ͞ΕΔɽ ͦͷޙɼσʔλϕʔ ਤ2 Kinect ͱύʔςΟΫϧϑΟϧλΛ༻͍ͨ࣌ྻܥσʔ λऔಘ εʹੵ͞Εͨ࣌ྻܥσʔλͱதؒදݱͷରԠؔΛ ػցֶश͢Δ͜ͱͰɼಈ࡞ผثΛੜ͢ΔɽςΩετ ੜʹ༻͍ΒΕΔݯࢿޠݴɼਓͷಈ࡞ͷදݱΛඃऀݧ ࣮ʹݧΑͬͯऩू͠ɼͦΕͧΕͷதؒදʹݱରͯ͠όΠ 3.1.1 ύʔςΟΫϧϑΟϧλ ύʔςΟΫϧϑΟϧλঢ়ଶͷ֬ີؔʹ୯ๆੑɾ άϥϜϞσϧΛߏங͢Δɽ͜ΕʹΑΓதؒදݱΛબ͢ Ψεੑͱ੍͍ͬͨͳ͘ɼඇઢܗɾඇΨεੑͷঢ় ΔͱɼͦͷதؒදʹݱରԠͨ͠όΠάϥϜϞσϧ͕બ ଶۭؒΛਪఆ͢Δ͜ͱ͕Ͱ͖Δɼ࣌ྻܥϑΟϧλͷ̍ͭ ͞ΕɼͦͷϞσϧʹಈతܭը๏Λద༻͢Δ͜ͱͰɼਓͷ Ͱ͋ΔɽίϯϐϡʔλϏδϣϯͷʹ͓͍ͯɼର ಈ࡞Λද͢ݱΔͬͱΒ͍͠ޠͷΈ߹ΘͤΛબͿ͜ ͳͲʹύʔςΟΫϧϑΟϧλΛͬͨख๏͕ଟ͘ ͱ͕Ͱ͖Δɽ ఏҊ͞Ε͍ͯΔɽύʔςΟΫϧϑΟϧλ, ؍ଌͰ͖ͳ ͍ঢ়ଶϕΫτϧ xt Λ؍ଌՄೳͳ؍ଌϕΫτϧ yt ͔Β 3.1 ࣌ྻܥσʔλͷऔಘͱॲཧ ਓؒͷಈ࡞ͷ࣌ྻܥσʔλɼKinect ΧϝϥΛ༻͍ ͯऔಘ͢ΔɽKinect ͷ։ൃ͋ͰݩΔ MicroSoft ࣾɼਓ ؒͷࠎ֨ΛਪఆͰ͖Δඪ४ϥΠϒϥϦఏ͓ͯ͠ڙΓɼ ͦͷϥΠϒϥϦΛ༻͍Δͱਓͷؔઅͷ 3 ࣍ݩใΛਪఆ ਪఆ͢Δɽঢ়ଶ xt ͱ؍ଌ yt , ͦΕͧΕҎԼʹࣔ͢ γεςϜϞσϧ (1), ؍ଌϞσϧ (2) ʹΑͬͯಘΒΕΔ. P (xt | xt−1 ) (1) P (yt | xt ) (2) ͢Δ͜ͱ͕Ͱ͖Δɽ (k) (k) K Λ༻͍ͨਓͷؔઅҐஔਪఆ༻͍ɼRGB ಈը૾ͱਓ K ݸͷॏΈ͚͞Εཻͨࢠͷू߹ Xt = {(xt , πt )}k=1 Ͱঢ়ଶ xt ͷࣄޙΛද͢. ͜͜Ͱ πt (k) ݸʑͷύʔ ͷݞͷӈखɾࠨखɾӈගɾࠨගɾݞͷத৺ͷ 5 Օॴͷ xyz ςΟΫϧͷॏΈΛ͍ࣔͯ͠Δ. ҰൠతͳύʔςΟΫϧ ຊͰڀݚɼRGB ը૾ͱਂηϯαʔɼ·ͨͦΕΒ 1 http://www.microsoft.com/en-us/kinectforwindows/ ϑΟϧλͷΞϦΰϦζϜΛҎԼʹࣔ͢. Proceedings of ARG WI2 step1 ॳظઃఆɿϥϯμϜͳ K ݸͷ xt−1 Λੜ͢Δɽ ͜ΕΛॳظύʔςΟΫϧͱ͢Δ (k) step2 ༧ଌɿࣜ (1) ʹै͍ xt (k) (k) Λ P (xt |xt−1 ) ͔ Βαϯϓϧ͢Δ (k) (k) (k) (k) step3 ࢉܭɿwt = P (yt |xt ) Кt = wt / (k) ͷΑ͏ʹཻ֤ࢠͷॏΈ Кt Λ͢ࢉܭΔ P (k) k wt step4 ϦαϯϓϦϯάɿπt ʹൺྫͨ֬͠Ͱ xt Λ K ݸநग़͢Δ ਤ4 ಈతܭը๏ʹΑΔϑϨʔϜׂΛ༻͍ͨ SAX ͷҰྫ step5 ࣌ؒߋ৽ɿt→t + 1 ͱͯ͠ step2ʙstep4 Λ܁ฦ͢ SAX ʹΑͬͯมͯ͠ಘΒΕͨจࣈྻ͔Βಈ࡞ͱΈ ΒΕΔॴݸΛऔΓग़͢ɽ͜͜Ͱɼ͋Δಈը૾σʔλத ͷશͯͷจࣈྻʹ͓͍ͯ 3 ͭલͷจࣈ͔ΒมԽ͕ͳ͚Ε ʮಈ͖͕ͳ͍ʯɼมԽ͕͋Εʮಈ͖͕͋ΔʯͱΈͳ ͢ (ਤ 5 ࢀর)ɽɹ ਤ 3 ύʔςΟΫϧϑΟϧλ ύʔςΟΫϧϑΟϧλ, ਤ 3 ʹࣔ͢Α͏ʹɼ༧ଌ, ࢉܭɼϦαϯϓϦϯάΛ܁ฦͯ࣌ؒ͠ߋ৽Λߦ͏. ͜ ͷΑ͏ʹͯ͠ɼ؍ଌ yt Λଟͷཻࢠ Xt ʹΑΓ ͍ͯ͘͠ɽຊͰڀݚɼମͷ৭Λࢉܭͷରͱ͢ Δ͜ͱͰɼମͷΛߦ͏ɽ 3.1.2 ࣌ྻܥσʔλͷॲཧ ਓͷࠎ֨ͱମͷ৭Λ͢Δ͜ͱͰಘΒΕͨ࣌ྻܥ σʔλɼSymbolic Aggregation approXimationʢSAXʣ [Lin 2003] Λ͍ɼจࣈྻʹม͢Δɽ SAX ͱɼ࣌ྻܥσʔλͷۙࣅදํݱ๏ͷ̍ͭͰɼ࣌ ྻܥσʔλΛจࣈྻʹม͢Δํ๏Ͱ͋ΔɽSAX Λߦ ͏ࡍɼ·ͣ PAA(Piecewise Aggregate Approximation) ͱ͍͏σʔλѹॖ࡞ۀΛߦ͏ɽ͞ n ͷ࣌ྻܥσʔλ C Λ༻͍ͯɼw ࣍ݩͷۭؒϕΫτϧ C̄ = c¯1 , . . . , c¯w ʹม ͢ΔͱԾఆ͢ΔɽC̄ ͷ i ൪ͷཁૉࣜ (3) Λ༻͍ͯ ͞ࢉܭΕΔɽ ਤ 5 ಈ͖ͷநग़ྫ ͦͷޙɼ ʮಈ͖͕͋ΔʯͱΈͳ͞ΕͨॴݸͷจࣈྻΛ มԽྔ (ਤ 6 தͷΞϧϑΝϕοτͷԼͷ) ʹม͠ɼ ѹॖ͢Δ (ਤ 7 ࢀর)ɽ͜Εಉ͡ಈ࡞ͰҐஔεϐʔ υʹΑͬͯจࣈྻ͕͋ΔҰఆͷִؒͰͣΕͨΓจࣈྻ ͷ͕͞มԽͨ͠Γͯ͠͠·͍ɼಉ͡ಈ͖ͱֶͯ͠श͞ Εͳ͍ͨΊͰ͋Δɽ͜ΕʹΑΓɼҰఆͷִؒͰͣΕͯ͠ ·ͬͨͷ͕͞ҧ͏ͷͰɼಉ͡ಈ͖ͱͯ͠ͱΒ ͑Δ͜ͱΛՄೳͱ͢Δɽ·ͨɼΑΓಛతͳಈ࡞Λநग़ ͢ΔͨΊʹɼѹॖ͞ΕͨมԽྔ͏ͪ࠷େͷେ͖͕͞ᮢ C̄i = w n X ʹຬͨͳ͍ͷऔΓআ͘ (ਤ 7 ࢀর)ɽ n wi Cj (3) n (i−1)+1 j= w ຊͰڀݚಈ࡞ผͷਫ਼ΛߴΊΔͨΊɼҰൠʹσʔ λΛִؒʹ w ݸͷϑϨʔϜʹׂ͢Δͱ͜ΖΛɼ֤ σʔλʹಈతܭը๏Λ༻͍ͬͱΒ͍۠͠ΓΛऔಘ ͢Δ͜ͱͰɼΑΓσʔλʹԊͬͨจࣈྻΛऔಘ͢Δ (ਤ 4 ࢀর)ɽ ਤ 6 จࣈྻͷมԽྔ Web ΠϯςϦδΣϯεͱΠϯλϥΫγϣϯڀݚձ༧ߘू SAX 䝕䞊䝍 䠴䠖cccccbbcccccc 䠵䠖aaabbeeeeeeee 䠶䠖dccbbaaaabbbc 䠴䠖cc 䠵䠖ee 䠶䠖cb ኚ㔞 䠴䠖0,0,0,0,-1,0,1,0,0,0,0,0 䠵䠖0,0,1,0,2,0,0,0,0,0,0,0 䠶䠖-1,0,-1,0,-1,0,0,0,1,0,0,1 䠴䠖0 䠵䠖0 䠶䠖-1 3.4 … όΠάϥϜϞσϧʹΑΔςΩετੜ ຊͰڀݚɼόΠάϥϜϞσϧΛ༻͍ͨ୯७ͳςΩε τੜΛߦ͏ɽͦΕͧΕͷಈ࡞ʹର͠όΠάϥϜϞσϧ Λߏங͢ΔͨΊʹඃݧ࣮ऀݧΛߦ͍ɼಛఆͷಈ࡞ʹର͠ … ༷ͯʑͳࣗવޠݴදݱΛूΊͨɽ͜ΕʹΑΓɼ؍ଌ͞Ε ͨ࣌ྻܥσʔλʹରͯ͠ಛఆͷதؒද͕ݱ༩͑ΒΕͨͱ ͖ɼͯ͠ͱݯࢿޠݴόΠάϥϜϞσϧΛબ͠ςΩετ 䠴䠖-1,1 䠵䠖3 䠶䠖-3,2 ᅽ⦰ 䠴䠖0 䠵䠖0 䠶䠖-1 ੜΛߦ͏ɽ ͔͠͠ɼྫ͑ಉ͡ಈ࡞Ͱɼ͋Δਓ 10 Ͱޠදݱ ͠ɼ·ͨ͋Δਓ 15 Ͱޠද͢ݱΔͳͲɼදݱͷํ͕ 䠴䠖-1,1 䠵䠖3 䠶䠖-3,2 㑅ู … … ҟͳΔɽจͷੜ֬ɼόΠάϥϜωοτϫʔΫ্Ͱ ͷબ͞Εͨ୯ޠͷੜͱ֬ى୯ؒޠͷભҠ֬ͷੵʹ Αܾͬͯ·ΔͨΊ จதʹ·ؚΕΔ͕ޠଟ͘ͳΔ΄Ͳ ਤ 7 σʔλͷѹॖɾબผͷྫ จͷੜ͕֬Լ͕ͬͯ͠·͏ɽ͜ͷ͜ͱ͔Βɼจͷ ͞ʹґଘ͠ͳ͍ςΩετੜ͕ߦ͑ΔΑ͏ɼόΠάϥϜ 3.2 தؒදݱ Ϟσϧʹ null ϥϕϧΛಋೖ͢Δɽ ςΩετੜͰɼ࣌ྻܥσʔλͱࣗવޠݴจΛͭͳ ͙தؒදݱΛ༻͍Δ͜ͱͰςΩετੜʹ͏ݯࢿޠݴ null ϥϕϧɼจͷதͷ୯ͯ͠ͱޠѻΘΕɼଞͷ୯ޠ ͱಉ͡Α͏ʹϢχάϥϜͱόΠάϥϜͷߏཁૉͱͳ Λબ͢Δɽதؒදݱද 1 ͷΑ͏ʹఆٛ͢Δɽ Δɽ͜ͷΑ͏ʹ null ϥϕϧΛѻ͏ͨΊʹɼߏ͞Εͨ ද1 action up όΠάϥϜϞσϧʹରͯ͠ಈతܭը๏Λద༻͢Δલʹ தؒදݱ தؒදݱ “up(joint,null)” ҎԼʹଓ͘લॲཧΛͦΕͧΕͷจʹରͯ͠ߦ͏ɽ·ͣɼ ҙຯ upward શͯͷจͰ୯ޠͷ࠷େ maxɼ࠷খ min ΛಘΔɽ movement ࣍ʹɼmax ͔Β min ΛҾ͖ɼnull ʹৼΔ൪߸ͷ࠷େ null max ΛٻΊΔɽ࠷ʹޙɼͦΕͧΕͷจʹର͠ɼ୯ ͕ޠmax ʹຬͨͳ͚Εɼnull max ͔Β 1 ͣͭҾ ͍ͨΛɼΓͳ͍͚ͩจ͔Βจ಄ʹ͚ૠೖͯ͠ down “down(joint,null)” downward movement pick “up(joint,object)” pick up movement put “down(joint,object)” put ͍͘ɽnull ϥϕϧಋೖͷΠϝʔδΛɼਤ 8 ʹࣔ͢ɽ move- ment 3.3 ࣌ྻܥσʔλͷಈ࡞ผ ຊͰڀݚਓͷಈ࡞ͷผΛߦ͏ͨΊʹରઢܗϞσ ϧΛ༻͍ɼॲཧ͞Εͨ࣌ྻܥσʔλͱதؒදݱͷରԠΛ ਤ 8 null ϥϕϧಋೖͷΠϝʔδ ػցֶशͤ͞Δɽ3.1 Ͱड़ͨ࣌ྻܥσʔλॲཧΛࢪ͠ ͨσʔλ d ͱɼਓͷಈ࡞Λද͢தؒද ݱr ͔Βߏͨ͠ ૉੑϕΫτϧ φ Λ༻͍ͯɼࣜ (4) ͷରઢܗϞσϧΛߏ ͢Δ͜ͱͰɼσʔλ͕༩͑ΒΕͨԼͰͷ֤தؒද͕ݱ બΕΔ֬ P (r|d) ΛϞσϧԽͨ͠ɽ͜͜ͰɼZd,w ਖ਼نԽͰ͋Δɽ จதͷ֤ null ϥϕϧʹҧ͏൪߸Λ͚ͭΔ͜ͱʹΑͬͯ ผͷ୯͠ͳݟͯ͠ͱޠɼͦΕͧΕ͕όΠάϥϜϞσϧͷ 1 ཁૉͱͯ͠ѻ͏ɽ·ͨɼຊͰڀݚόΠάϥϜϞσϧ Λߏங͢Δࡍʹɼ༻͢ΔจͷऔࣺબΛߦΘͳ͍͜ͱ Ͱɼଟ͘ͷؔͱޠ࿈͚ͮΔ͜ͱ͕Ͱ͖ΔͨΊɼΑΓෳࡶ ͳςΩετੜΛߦ͏͜ͱ͕Ͱ͖Δɽ P (r|d) = 1 Zd,w exp(w · φ(d, r)) (4) ਓͷಈ࡞Λઆ໌͢ΔͷʹΑ͘༻͍ΒΕΔจΛੜ͢Δ ͨΊʹɼ͜ͷόΠάϥϜϞσϧʹಈతܭը๏Λద༻͢ Δ͜ͱͰ͕࠷ߴ͘ͳΔ୯ޠͷΈ߹Θ͔ͤΒͳΔ จΛબͿɽ Proceedings of ARG WI2 ࣮ݧ 4 4.2 ߏஙͨࣝ͠ผػΛ༻͍ͯςετσʔλ͔Βผ͞Εͨ ͜͜Ͱɼ ʮखΛ্͛ΔʯʮखΛԼ͛ΔʯʮϘʔϧΛऔ ΔʯʮϘʔϧΛஔ͘ʯͱ͍͏؆୯ͳಈ࡞ (ਤ 9) Λݴ༿Ͱ ࣮݁ݧՌ தؒදݱɼॱʹ ද͢ݱΔ͜ͱΛతͱ͢Δɽ 1. “up((left hand),null)” 2. “up((right hand),null)” 3. “down((left hand,right hand),null)” 4. “up((right hand),green)” ਤ 9 ޠݴԽͷରͱͳΔಈ࡞ 5. “down((right hand),green)” 4.1 ࣮༷ݧ 6. “up((left hand,right hand),null)” ޠݴԽͷରͱͳΔಈ࡞ΛʮࠨखΛ͋͛ΔʯʮӈखΛ ্͛Δʯʮ྆खΛԼ͛ΔʯʮϘʔϧΛऔΔʯʮϘʔϧΛஔ 7. “down((right hand),null)” ͘ʯʮ྆खΛ্͛ΔʯʮӈखΛԼ͛ΔʯʮࠨखΛԼ͛Δʯ 8. “down((left hand),null)” ͷ 8 ͭͷجຊಈ࡞͔ΒΔͱఆٛ͢Δɽ·ͨɼͦΕͧΕ ͷಈ࡞ʹର͠ɼࣗવͰޠݴͷઆ໌จΛੜ͢Δ͜ͱͱ͢ ͱͳͬͨɽ࣍ʹɼબΕͨதؒදʹݱରͯ͋͠Β͔͡Ί Δɽඃͯ͠ͱݧ࣮ऀݧɼରͱͳΔਓͷಈ࡞ͷ Kinect ߏங͞ΕͨόΠάϥϜϞσϧʹಈతܭը๏Λద༻͢Δ͜ ϏσΦΛ؍͠ɼͦΕʹ͍ͭͯࣗવͰޠݴઆ໌ͯ͠Β ͱͰɼಈ࡞Λઆ໌͢ΔͬͱΒ͍͠จΛੜ͢Δɽ ͏ͱ͍͏࣮ݧΛ 12 ਓʹର͠ߦͬͨɽऩूͨ͠ຊޠͷ આ໌จΛܗଶૉղੳ ػMeCab Λ༻͍ͯ୯ʹͱ͝ޠ͚ɼ ݁Ռͱͯ͠ɼͦΕͧΕͷಈ࡞ʹରͯ͠ͷߴ͔ͬͨ ্Ґ 3 จΛද 3 ʹࣔ͢ɽ ͜ΕΛͯ͠ͱݯࢿޠݴόΠάϥϜϞσϧΛߏஙͨ͠ɽݴ ͨͬͳͱݯࢿޠઆ໌จͷશจɼޠɼޠͷछྨΛද 2 ʹࣔ͢ɽ 4.3 ߟ ࣮݁ݧՌ͔Βɼਓͷಈ࡞Λਖ਼֬ʹද͢ݱΔจ͕ੜग़ ද 2 ऩू͞Εͨจͷಛ དྷ͍ͯΔ͜ͱ͕֬ೝͰ͖ͨɽ·ͨɼද 3 ͷੜจΛΈ ಈ͖ จ ޠ ޠͷछྨ Δͱɼ͍͔ͭ͘ͷจͰऴจࣈ ʮEOFʯ͕ग़͖͍ͯͯ ࠨखΛ্͛Δ 27 145 43 ͳ͍͜ͱ͕͔Δɽ͜ΕɼόΠάϥϜϞσϧ͕ूΊͨ ࠨखΛԼ͛Δ 28 146 47 จʹݱΕΔޠͷόΠάϥϜͷΈ߹ΘͤʹΑͬͯߏ͞ ӈखΛ্͛Δ 25 131 44 Ε͍ͯΔͨΊͰ͋Δɽ͜ΕʹΑΓɼόΠάϥϜϞσϧ ӈखΛԼ͛Δ 31 174 51 null ϥϕϧΛՃ͑ͨจ͕ɼूΊΒΕͨͲͷจΑΓ͘ ྆खΛ্͛Δ 32 163 50 ੜ͞ΕΔՄೳੑ͕͋Δɽ·ͨҰํͰɼจ͕͘ͳΕ ྆खΛԼ͛Δ 30 165 53 ͳΔ΄Ͳɼͦͷจͷ͕͘ͳ͍ͬͯ͘ɽ͕ͨͬͯ͠ɼ ϘʔϧΛऔΔ 29 162 37 ूΊΒΕͨจΑΓ͍จੜ͞Εͳ͍ͱ͍͏ԾఆͷԼ ϘʔϧΛஔ͘ 29 170 43 ͰɼूΊͨจͷ࠷େͷ୯ޠΛੜจͷ୯ͨ͠ͱޠɽ ςετσʔλʹɼ ʮࠨखΛ͋͛ΔʯʮӈखΛ্͛Δʯ 5 ·ͱΊͱࠓޙͷ՝ ʮ྆खΛԼ͛Δʯ ʮϘʔϧΛऔΔʯ ʮϘʔϧΛஔ͘ʯ ʮ྆ख ຊͰڀݚɼಈը૾தͷਓͷಈ࡞Λද͢ݱΔ֬తݴ Λ্͛Δʯ ʮӈखΛԼ͛Δʯ ʮࠨखΛԼ͛ΔʯͷॱͰಈ࡞ ޠੜͷΈΛఏҊͨ͠ɽKinect ϏσΦͰநग़͞Ε Λߦͬͨ Kinect ಈըΛ༻ͨ͠ɽಈ࡞ผʹ 3.3 Ͱ ͨਓͷಈ࡞͓ΑͼύʔςΟΫϧϑΟϧλͰऔಘ͞Εͨ ࣔͨ͠ରઢܗϞσϧΛద༻͠ɼςΩετੜʹΘΕ ମͷيɼ࣌ྻܥσʔλͱͯ͠औಘ͞ΕɼSAX ʹಈ Δதؒදݱͷผʹ༻͍ͨɽ తܭը๏Λ༻͍ͬͱΒ͍۠͠ΓΛಋೖͯ͠߸هԽ ͢Δख๏ͳͲɼ͍͔ͭ͘ͷ࣍ݩѹॖख๏Λద༻͢Δ͜ͱ Ͱػցֶशʹదͨ͠ʹܗม͞ΕΔɽ·ͨ؍ଌ͞Εͨਓ ͷಈ͖Λද͢ݱΔͨΊʹɼඃʹݧ࣮ऀݧΑͬͯूΊΒΕ ͨࣗવޠݴจʹ͖ͮجόΠάϥϜϞσϧΛߏங͠ɼಈత ܭը๏Λద༻͢Δ͜ͱͰɼͬͱΒ͍͠ޠͷΈ߹Θ ͤΛऔಘ͢Δɽ͞ΒʹɼόΠάϥϜϞσϧʹ൪߸Λ͚ Web ΠϯςϦδΣϯεͱΠϯλϥΫγϣϯڀݚձ༧ߘू ද 3 ֤ಈ࡞ʹର͢Δੜจͷ্Ґ 3 จ ಈ࡞ 1 2 3 4 5 6 7 8 • • • • • • • • • • • • • • • • • • • • • • • • ੜจ ࠨख, Λ, ্͛Δ, ɻ, null 5, null 6, null 7, null 8, EOF ࠨख, Λ, ্͛Δ, ɻ, null 4, null 5, null 6, null 7, null 8 ࠨख, Λ, ͻ͡, Λ, ্͛Δ, ɻ, null 4, null 5, null 6 ӈख, Λ, ্͛Δ, ɻ, null 4, null 5, null 6, null 7, null 8 ӈख, Λ, ্͛Δ, ɻ, null 5, null 6, null 7, null 8, EOF ӈख, Λ, ͢͜͠, ͋͛Δ, ɻ, null 4, null 5, null 6, null 7 ྆ख, Λ, ԼΖ͢, ɻ, null 4, null 5, null 6, null 7, null 8, null 9 ྆ख, Λ, ԼΖ͢, ɻ, null 5, null 6, null 7, null 8, null 9, EOF ྆ख, Λ, ಉ࣌ʹ, Լ͛Δ, ɻ, null 4, null 5, null 6, null 7, null 8 Ϙʔϧ, Λ, ্࣋ͪ͛Δ, ɻ, null 5, null 6, null 7, null 8, null 9, EOF ࠨख, Ͱ, Ϙʔϧ, Λ, ্࣋ͪ͛Δ, ɻ, null 6, null 7, null 8, null 9 Ϙʔϧ, Λ, ࠨख, Ͱ, Ϙʔϧ, Λ, ্࣋ͪ͛Δ, ɻ, null 6, null 7 Ϙʔϧ, Λ, ஔ͘, ɻ, null 5, null 6, null 7, null 8, null 9, EOF Ϙʔϧ, Λ, ஔ͘, ɻ, null 4, null 5, null 6, null 7, null 8, null 9 ࠨख, Ͱ, Ϙʔϧ, Λ, ஔ͘, ɻ, null 5, null 6, null 7, null 8 ྆ख, Λ, ্͛Δ, ɻ, null 5, null 6, null 7, null 8, null 9, EOF | ྆ख, Λ, ্͛Δ, ɻ, null 4, null 5, null 6, null 7, null 8, null 9 ྆ख, Λ, ಉ࣌ʹ, ͛ڍΔ, ɻ, null 4, null 5, null 6, null 7, null 8 ӈख, Λ, ԼΖ͢, ɻ, null 4, null 5, null 6, null 7, null 8 ӈख, Λ, ԼΖ͢, ɻ, null 5, null 6, null 7, null 8, EOF ӈख, Λ, ހ, Λ, ԼΖ͢, ɻ, null 4, null 5, null 6 ࠨख, Λ, Լ͛Δ, ɻ, null 4, null 5, null 6, null 7, null 8, null 9, null 10 ࠨख, Λ, Լ͛Δ, ɻ, null 5, null 6, null 7, null 8, null 9, null 10, EOF ࠨख, Λ, ৳͠, ͨ, ɻ, null 4, null 5, null 6, null 7, null 8, null 9 ͨ null ϥϕϧΛಋೖ͢Δ͜ͱʹΑΓɼจੜʹ୯ޠ ͷ੍ݶΛ͚ͭͣʹࣗવޠݴจੜΛߦ͏͜ͱ͕Ͱ͖ͨɽ ·ͨɼఏҊख๏ςϯϓϨʔτʹΑΔςΩετੜͰ [5] ͳ͘ɼ֬తͳϞσϧʹΑΔੜͰ͋Δ͜ͱ͔Βɼྫ͑ ͞ΒʹจΛऩू͢ΕͦΕʹ߹Θͤͯग़ྗจมԽ͠ [6] ͍ͯ͘ͳͲɼࢿͳͱݯΔจॻʹΑ༷ͬͯʑͳࣗવޠݴද ݱΛಘΔ͜ͱ͕Ͱ͖Δɽ ҰํͰɼݱஈ֊Ͱߏจ੍ΛऔΓೖΕ͍ͯͳ͍ɽ [7] ͦͷͨΊࠓޙͷ՝ͱͯ͠ɼ͜͏ͨࣝ͠Λಋೖ͢Δͱ ͱʹɼΑΓਖ਼֬ʹΠϕϯτΛઆ໌͢ΔΑ͏ͳςΩετ ੜ͕ߦ͑ΔΑ͏ൃల͍͖͍ͤͯͨ͞ͱߟ͑Δɽ·ͨɼ [8] தؒදͱݱόΠάϥϜϞσϧͱͷରԠ͚ΛΑΓॊೈ͠ ͨΓɼҰ࿈ͷಈ࡞͔ΒࣗવޠݴจʹΑͬͯઆ໌͞ΕΔಈ ࡞Λ۠ΔʹऔΓΜͰ͍͖͍ͨɽ [9] ࢀߟจݙ [1] Haonan Yu and Jeffrey Mark Siskind, Grounded Language Learning from Video Described with Sentences, 51th Associcatoin for Computational Linguistics, Bulgaria, 2013. [2] Regneri,M., Rohrbach,M., Wetzel,D.,Thater, S., Schiele, B., and Pinkal, M., Grounding Action Descriptions in Videos, 51th Associcatoin for Computational Linguistics, Bulgaria, 2013. [3] Yoshitaka Ushiku, Tatsuya Harada, and Yasuo Kuniyoshi. A Understanding Images with Natural Sentences. the 19th Annual ACM International Conference on Multimedia (ACMMM 2011), pp.679-682, 2011. [4] Takano, W. and Nakamura, Y.:Integrating whole body motion primitives and natural language for [10] 1.76e-12 1.57e-12 1.19e-14 8.63e-13 5.40e-13 3.98e-15 2.91e-14 2.68 e-14 1.49e-16 2.64e-14 2.03e-14 2.77e-15 3.99e-15 2.79 e-15 2.57e-16 2.53e-14 1.41e-14 1.32e-15 2.05e-12 5.96e-13 3.71e-15 2.67e-15 8.90e-16 9.53e-18 humanoid robots, Proc. IEEE-RAS Int. Conf. Humanoid Robots, pp.708-713, 2008. Takano, W. and Nakamura, Y.:Incremental learning of integrated semiotics absed on linguistic and behavioral symbols, Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp.1780-1785, 2010. Percy Liang, Michael I. Jordan, Dan Klein 2009. Learning Semantic Correspondences with Less Supervision, ACL-IJCNLP Angeli, Gabor and Liang, Percy and Klein, Dan, 2010. A simple domain-independent probabilistic approach to generation, Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 502–512,Cambridge, Massachusetts Konstas, Ioannis and Lapata, Mirella, 2012. Unsupervised concept-to-text generation with hypergraphs, Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Montreal, Canada, pp.752–761 Konstas, Ioannis and Lapata, Mirella, 2012. Concept-to-text generation via discriminative reranking, Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1, pp. 369–378, Jeju Island, Korea Lin, J., Keogh, E., Lonardi, S. and Chiu, B. 2003. A Symbolic Representation of Time Series, with Implications for Streaming Algorithms DMKD’ 03
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