• 検索結果がありません。

法線分布関数フィルタリングの実装と評価

N/A
N/A
Protected

Academic year: 2021

シェア "法線分布関数フィルタリングの実装と評価"

Copied!
4
0
0

読み込み中.... (全文を見る)

全文

(1)Vol.2016-CG-164 No.2 2016/9/21. ৘ใॲཧֶձ‫ڀݚ‬ใࠂ IPSJ SIG Technical Report. ๏ઢ෼෍ؔ਺ϑΟϧλϦϯάͷ࣮૷ͱධՁ ಙ٢ ༤հ1,a). ֓ཁɿຊߘ͸ 2016 ೥ʹൃද͞Εͨ Kaplanyan et al. ͷ‫ڸ‬໘൓ࣹͷΞϯνΤΠϦΞγϯάख๏ͷ࣮૷ͱධ Ձʹ͍ͭͯใࠂ͢Δɽ͜ͷख๏͸ࢹઢํ޲ͱޫ‫޲ํݯ‬ͷதؒϕΫτϧͷඍ෼Λ༻͍ͯ๏ઢ෼෍ؔ਺ΛϑΟ ϧλϦϯά͢Δͱ͍͏΋ͷͰ͋Δɽ͔࣮͠͠ࡍʹ͸ඍ෼ͷਪఆ‫͕ࠩޡ‬େ͖͍ͨΊɼ๬·͍݁͠ՌΛಘΒΕ ͳ͍͜ͱ͕ଟ͍ɽ͜ͷ͜ͱ͸ Kaplanyan et al. ΋࿦จதͰࢦఠ͓ͯ͠Γɼ࣮༻ʹ͸ϑΟϧλϦϯάʹόΠ ΞεΛՃ͑ͯਖ਼֬͞ΑΓ҆ఆੑΛ༏ઌ͢Δ͜ͱΛਪ঑͍ͯ͠Δɽͦ͜Ͱզʑ͸ͲͷΑ͏ͳόΠΞεΛՃ͑ Δͷ͕࣮༻తͳͷ͔ௐ΂ΔͨΊɼ࣮‫ݧ‬Λߦͬͨɽͦͷ݁ՌɼσΟϑΝʔυϨϯμϦϯά޲͚ͷۙࣅख๏͕ ࠷΋҆ఆ͍ͯ͠Δ͜ͱ͕෼͔ͬͨɽ. Evaluation of Normal Distribution Function Filtering for Specular Anti-Aliasing Tokuyoshi Yusuke1,a). 1. ๏ઢ෼෍ؔ਺ͷϑΟϧλϦϯά.  Σ=σ. 2. ϩʔϓεϖʔεʹ͓͚Δඍ෼Λ༻͍ͯ๏ઢ෼෍ؔ਺ΛϑΟ ϧλϦϯά͢Δख๏ΛఏҊͨ͠ɽ͔͠͠ͳ͕Βɼ࣮ࡍʹ͸ ඍ෼ͷਪఆ͸ෆ҆ఆͰ‫͕ࠩޡ‬େ͖͘ͳΓ΍͍͢ɽͦͷͨ Ίɼ࣮༻ʹ͸ϑΟϧλϦϯάʹόΠΞεΛՃ͑Δ͜ͱ͕ਪ ঑͞Ε͍ͯΔɽͦ͜ͰຊߘͰ͸ͲͷΑ͏ͳόΠΞεΛՃ͑ Δͷ͕࣮༻తͳͷ͔Λ‫͢ূݕ‬Δɽ. ΕΔɽਪఆ͞ΕͨεϩʔϓεϖʔεͰͷதؒϕΫτϧͷ ඍ෼ʢϐΫηϧؒͷࠩ෼ʣΛ Δhu , Δhv ͱ͠ɼϐΫηϧͷ ϑΟϧλϦϯάΧʔωϧΛ෼ࢄ σ 2 = 0.25 ͷΨ΢ε෼෍ͱ Ծఆ͢ΔͱɼεϩʔϓεϖʔεͰͷதؒϕΫτϧͷ‫ڞ‬෼ࢄ ߦྻ͸ҎԼͷࣜͰ༩͑ΒΕΔɽ 1 a). ‫ࣜג‬ձࣾεΫ΢ΣΞɾΤχοΫε [email protected]. ⓒ 2016 Information Processing Society of Japan. . Δhv. .. (1). ͢ΔɽBeckmann ෼෍͸εϩʔϓεϖʔεͰ͸Ψ΢ε෼෍ Ͱ͋Γɼ‫ڸ‬໘ͷૈ͞ύϥϝʔλͷೋ৐ α2 ͸๏ઢ෼෍ͷ෼ ࢄΛೋഒͨ͠΋ͷͰ͋ΔɽதؒϕΫτϧͷ෼෍͸ϚΠΫϩ ϑΝηοτͷ๏ઢ෼෍ͳͷͰɼϑΟϧλϦϯάΛղੳతͳ ৞ΈࠐΈʹΑͬͯද͢͜ͱ͕Ͱ͖Δɽͦͷ݁ՌɼϑΟϧλ Ϧϯά‫ޙ‬ͷ‫ڸ‬໘ͷૈ͞͸ҎԼͷߦྻͱͳΔɽ.  A=. α2. 0. 0. α2. ͷਪఆ͸ɼϐΫηϧγΣʔμʔͰྡ઀ϐΫηϧͱͷࠩ෼Λ R ‫ٻ‬ΊΔ໋ྩʢe.g., DirectX Ͱ͸ ddx/ddyʣʹΑͬͯߦΘ. Δhu. ࣍ʹ෺ମද໘ͷ๏ઢ෼෍ؔ਺Λ Beckmann ෼෍ [1] ͱԾఆ. 1.1 ख๏ ϦΞϧλΠϜϨϯμϦϯάʹ͓͚ΔதؒϕΫτϧͷඍ෼. T . Δhv. Kaplanyan et al. [4] ͸‫ڸ‬໘൓ࣹͷΞϯνΤΠϦΞγϯ άΛߦ͏ͨΊʹɼࢹઢํ޲ͱޫ‫޲ํݯ‬ͷதؒϕΫτϧͷε. Δhu.  + 2Σ.. (2). ۙ೥өը΍ήʔϜ౳ͰҰൠతʹ࢖༻͞Ε͍ͯΔ GGX ෼ ෍ [7], [8] ͷૈ͞ύϥϝʔλ͸ɼBeckmann ෼෍ͷૈ͞ύϥ ϝʔλͰۙࣅՄೳͰ͋ΔɽͦͷͨΊຊߘͰ͸͜ͷૈ͞ߦྻ. A Λ GGX ෼෍ʹద༻͢Δɽ ঘɼૈ͞ߦྻΛ࢖ͬͯҰൠԽͨ͠ GGX ૒ํ޲൓ࣹ཰ ෼෍ؔ਺ʢbidirectional reflectance distribution function,. BRDFʣʹ͍ͭͯ͸‫ݩ‬࿦จʹ‫͞ࡌه‬Ε͍ͯͳ͍ɽͦͷͨΊɼ ใࠂऀ͕ಋग़ΛߦͬͨࣜΛ §A.1 ʹ‫ه‬ड़͢Δɽ. 1.

(2) Vol.2016-CG-164 No.2 2016/9/21. ৘ใॲཧֶձ‫ڀݚ‬ใࠂ IPSJ SIG Technical Report. 1.2 ό΢ϯσΟϯάϘοΫεΛ࢖ͬͨϑΟϧλϦϯά લड़ͷख๏͸ཧ࿦తʹ͸ਖ਼͍͕͠ɼ࣮ࡍʹ͸‫ࠩޡ‬ͷӨ‫ڹ‬ Λ‫͘ڧ‬ड͚ΔͷͰ๬·͍݁͠ՌΛಘΒΕͳ͍͜ͱ͕͋Δ. }. ͨͩ͠ɼ๏ઢ෼෍ؔ਺ϑΟϧλϦϯάͰ͸ॎԣͷϐΫη ϧͷมԽྔΛ‫ݟ‬ΔͷͰɼର֯ํ޲ͷϐΫηϧͷ๏ઢ͸ແ͘ ͯ΋ྑ͍ɽͦͷͨΊຊߘͰ͸ҎԼͷΑ͏ʹলུͨ͠ɽ. ͱ‫ݩ‬࿦จͰड़΂ΒΕ͍ͯΔɽͦ͜ͰϑΟϧλϦϯάΛ҆ఆ. float3 SumNeighborPixels( float2 pixelID, float3 normal ). ͤ͞ΔͨΊʹɼKaplanyan et al. ͸όΠΞεͷ͋Δա৒ͳ. { float2 dir = 1.0 - 4.0 * frac( pixelID * 0.5 );. ϑΟϧλϦϯάΛ࢖͏͜ͱΛਪ঑ͨ͠ɽ͜Ε͸ Δhu , Δhv. float3 horz = normal + ddx_fine( normal ) * dir.x;. Ͱ࡞ΒΕΔฏߦ࢛ล‫ܗ‬ͷό΢ϯσΟϯάϘοΫεͷॎԣͷ. float3 vert = normal + ddy_fine( normal ) * dir.y;. ෯Λҟํੑ BRDF ͷૈ͞ύϥϝʔλͱͯ͠࢖͏ͱ͍͏΋ ͷͰ͋Δɽ. return normal + horz + vert; }. 2.1.2 HLSL Shader Model 6.0 1.3 ࣮‫݁ݧ‬Ռ ࣮‫݁ݧ‬ՌΛਤ 1 ʹࣔ͢ɽ͜ͷϑΟϧλϦϯάख๏ʹΑͬ ͯΤΠϦΞγϯάΛ཈͑Δ͜ͱ͕Ͱ͖ͨҰํͰɼೖࣹ͕֯ ઙ͍৔߹ʹա৒͔ͭҟํੑͷ‫͍ڧ‬ϑΟϧλϦϯά͕ߦΘΕ ͓ͯΓɼ͜ΕʹΑͬͯ‫ʹٯ‬ΞʔςΟϑΝΫτ͕ൃੜͯ͠͠. DirectX 12 ͷ HLSL Shader Model 6.0 Ͱ͸ྡ઀ϐΫη ϧͷ஋Λ௚઀ࢀর͢Δ໋ྩ͕௥Ճ͞Εͨɽ͜ΕΛ༻͍Δ͜ ͱͰ্ड़ͷ pixel quad message passing ๏ΑΓ΋୯७͔ͭ ਫ਼౓ͷߴ͍ฏ‫ۉ‬஋Λ‫ٻ‬ΊΔ͜ͱ͕ՄೳʹͳΔͱߟ͑ΒΕΔɽ ࠓ‫ޙ‬͸͜ͷ৽໋ྩΛ࢖࣮ͬͨ૷Λߦ͍͍ͨͱߟ͍͑ͯΔɽ. ·͍ͬͯΔɽ͜ͷ‫ݪ‬Ҽ͸εϩʔϓεϖʔεʹ͓͚Δதؒϕ ΫτϧͷมԽྔ͕ೖࣹ֯ͷਖ਼઀ʹൺྫ͢ΔͨΊͩͱߟ͑Β ΕΔɽͦͷͨΊɼೖࣹ͕֯ઙ͘‫ͭ׌‬๏ઢ͕ϐΫηϧؒͰม Խ͢Δ৔߹ɼ͜ͷதؒϕΫτϧͷมԽྔͷ‫ۃ͕ࠩޡ‬Ίͯେ ͖͘ͳͬͯ͠·͏Α͏Ͱ͋Δɽ͜͏ͨ͠ΞʔςΟϑΝΫτ ͸ Kaplanyan et al. ͕ओு͢ΔΑ͏ʹό΢ϯσΟϯάϘο ΫεΛ࢖ͬͨϑΟϧλϦϯάͰܰ‫ݮ‬ՄೳͰ͋Δɽ͠ͳ͠ͳ ͕ΒɼͦΕͰ΋ґવͱͯ͠໨ཱͭΞʔςΟϑΝΫτ͕ൃੜ ͯ͠͠·͍ͬͯΔɽ. 2. ฏ‫ۉ‬๏ઢϕΫτϧΛ༻͍ͨۙࣅ தؒϕΫτϧΛ༻͍ͨϑΟϧλϦϯά͸ޫ‫ݯ‬ຖʹ‫͢ࢉܭ‬ Δඞཁ͕͋Γɼޫ‫͕਺ݯ‬ଟ͍৔߹ʹ‫͕ྔࢉܭ‬ଟ͘ͳΔɽ· ͨɼσΟϑΝʔυϨϯμϦϯάʹ༻͍Δ͜ͱ͕Ͱ͖ͳ͍ͱ ͍͏໰୊͕͋Δɽͦ͜ͰσΟϑΝʔυϨϯμϦϯάʹର͠ ͯ͸ɼதؒϕΫτϧͷ୅ΘΓʹۙ๣ 4 ϐΫηϧͷ๏ઢͷฏ ‫ۉ‬Λ༻͍Δۙࣅ͕ఏҊ͞Ε͍ͯΔɽͦ͜Ͱ͜ͷۙࣅ๏ʹͭ ͍ͯ඼࣭ͷධՁΛߦͬͯΈΔ͜ͱʹͨ͠ɽۙ๣ 4 ϐΫηϧ ͷ๏ઢϕΫτϧͷฏ‫ۉ‬ͷ‫ٻ‬Ίํ͸‫ݩ‬࿦จʹ‫ه‬ड़͞Ε͍ͯͳ ͍ͷͰɼຊߘͰղઆ͢Δɽ. 2.2 ࣮‫݁ݧ‬Ռ ࣮‫݁ݧ‬ՌΛਤ 2 ʹࣔ͢ɽ‫ʹͱ͖͜΂͘ڻ‬ೖࣹ͕֯ઙ͍৔ ߹ͰͷΞʔςΟϑΝΫτͷൃੜΛ཈͑Δ͜ͱ͕Ͱ͖ͨɽ͜ ͷཧ༝ͱͯ͠͸ɼதؒϕΫτϧͱҟͳΓฏ‫ۉ‬๏ઢ͸෺ମද ໘ʹରͯ͠ઙ͘ͳΓʹ͍ͨ͘Ίͱߟ͑ΒΕΔɽͦͷͨΊɼ ཧ࿦্͸தؒϕΫτϧΛ༻͍Δͷ͕ਖ਼͍͠ͱߟ͑ΒΕΔ͕ɼ ฏ‫ۉ‬๏ઢϕΫτϧΛ༻͍ͨํ͕࣮༻ੑ͸ߴ͍ͱ‫͑ݴ‬Δɽ. 3. ౳ํੑۙࣅ σΟϑΝʔυϨϯμϦϯάͰ͸ɼG-buffer [6] ͷϝϞϦʔ ࢖༻ྔΛ཈͑ΔͨΊ౳ํੑͷૈ͞ύϥϝʔλʹͨ͠ํ͕๬ ·͍͠ɽͦ͜Ͱ Kaplanyan et al. ͕ओு͢ΔΑ͏ʹɼό΢ ϯσΟϯάϘοΫεΛ࢖ͬͨϑΟϧλϦϯάʹ͓͍ͯૈ͞ ͷ࠷େ஋Λ༻͍ͨ౳ํੑϑΟϧλϦϯάΛߦͬͬͯΈΔ͜ ͱʹͨ͠ɽ·ͨ௥Ճ࣮‫ͯ͠ͱݧ‬ɼ‫ڞ‬෼ࢄߦྻͷ࠷େͷ‫ݻ‬༗ ஋Λ༻͍ͯૈ͞ͷਪఆΛߦͬͯΈͨɽ. 3.1 ࣮‫݁ݧ‬Ռ ࣮‫݁ݧ‬ՌΛਤ 3 ʹࣔ͢ɽҟํੑϑΟϧλϦϯάͱҟͳ Γɼ྆ऀͱ΋ࢹ֮తʹෆշͳΞʔςΟϑΝΫτ͕ൃੜ͢Δ. 2.1 ࣮૷ 2.1.1 Pixel quad message passing ϐΫηϧγΣʔμʔʹ͓͍ͯɼྡ઀ϐΫηϧͷ஋Λಘ Δํ๏ͱͯ͠ pixel quad message passing ๏ [5] ͕͋Δɽ DirectX Ͱ͸ྡ઀ϐΫηϧͷ஋ͱͷਖ਼֬ͳࠩ෼ΛಘΔ໋ྩ ͱͯ͠ɼddx fine/ddy fine ໋ྩ͕͋Δɽ͜ΕΛ༻͍Δ͜ͱ ͰɼҎԼͷΑ͏ʹ 4 ϐΫηϧͷ๏ઢͷ૯࿨Λ‫ٻ‬ΊΔ͜ͱ͕ ՄೳͱͳΔɽ float3 SumNeighborPixels( float2 pixelID, float3 normal ) {. ͜ͱ͸ͳ͘ͳͬͨɽҰํͰɼશମతʹա৒ͳϑΟϧλϦϯ ά͕ߦΘΕͯ͠·͍ͬͯΔɽ͔͠͠ͳ͕ΒதؒϕΫτϧΛ ༻͍ͨҟํੑͷϑΟϧλϦϯάͱҧ͍ɼߴप೾ͷΞʔςΟ ϑΝΫτͰ͸ͳ͍ͷͰࢹ֮తʹ‫ڐ‬༰͠қ͍ͱߟ͑ΒΕΔɽ. Kaplanyan et al. ͕ఏҊ͍ͯ͠Δૈ͞ͷ࠷େ஋Λ༻͍ΔΑ Γ΋ɼ࠷େͷ‫ݻ‬༗஋Λ༻͍ͯૈ͞Λਪఆͨ͠ํ͕ա৒ͳ ϑΟϧλϦϯάΛए‫ׯ‬཈͑Δ͜ͱ͕Ͱ͖ͨɽ. 4. ·ͱΊ. float2 dir = 1.0 - 4.0 * frac( pixelID * 0.5 ); float3 horz = normal + ddx_fine( normal ) * dir.x;. ຊ‫ڀݚ‬ใࠂͰ͸ Kaplanyan et al. ͷ๏ઢ෼෍ؔ਺ϑΟϧ. float3 vert = normal + ddy_fine( normal ) * dir.y;. λϦϯάͷ࣮૷ͱධՁΛߦͬͨɽ࣮‫ݧ‬ͷ݁Ռɼཧ࿦௨Γͷ. float3 diag = horz + ddy_fine( horz ) * dir.y; return normal + horz + vert + diag;. ⓒ 2016 Information Processing Society of Japan. ࣮૷Ͱ͸ߴप೾ͷΞʔςΟϑΝΫτ͕ൃੜ͢Δ͜ͱ͕֬. 2.

(3) Vol.2016-CG-164 No.2 2016/9/21. ৘ใॲཧֶձ‫ڀݚ‬ใࠂ IPSJ SIG Technical Report. (a) ϑΟϧλϦϯάແ͠. (b) ‫ڞ‬෼ࢄߦྻΛ࢖ͬͨϑΟϧλϦϯά. (c) ό΢ϯσΟϯάϘοΫεΛ࢖ͬͨϑΟϧλ Ϧϯά. ਤ 1: தؒϕΫτϧͷඍ෼Λ༻͍ͨҟํੑϑΟϧλϦϯάɽೖࣹ͕֯ઙ͍৔߹ʹෆշͳΞʔςΟϑΝΫτ͕ൃੜ͍ͯ͠Δɽ ೝ͞Εͨɽ͔͠͠ͳ͕Βɼۙࣅख๏Ͱ͋ΔσΟϑΝʔυϨ ϯμϦϯά޲͚ͷ౳ํੑϑΟϧλϦϯάͰ͸ɼ෭࡞༻ͱ͠ ͯ͜ΕΒͷ໰୊ΛճආՄೳͰ͋Δ͜ͱ͕෼͔ͬͨɽͦͷͨ ΊɼϑΥϫʔυϨϯμϦϯάͰ͋ͬͯ΋ɼ͜ͷσΟϑΝʔ υϨϯμϦϯά޲͚ͷۙࣅΛߦͬͨํ͕ྑ͍Մೳੑ͕͋ Δɽ͜ͷۙࣅख๏͸ա৒ͳϑΟϧλϦϯάʹΑͬͯେ͖ͳ όΠΞεΛੜΈग़͕͢ɼ͜ͷόΠΞε͸௿प೾Ͱ͋Δɽ͜ ͷΑ͏ͳ௿प೾ͷόΠΞε͸ࢹ֮తʹෆշʹͳΓʹ͍͘ͷ ͰɼήʔϜ౳ͷ‫ָޘ‬Λ໨తͱͨ͠ΞϓϦέʔγϣϯʹର͠ (a) ‫ڞ‬෼ࢄߦྻΛ࢖ͬͨϑΟϧλ (b) ό΢ϯσΟϯάϘοΫεΛ Ϧϯά. ࢖ͬͨϑΟϧλϦϯά. ͯ͸ద͍ͯ͠ΔՄೳੑ͕͋Δɽ ँࣙ. ຊ࿦จͷϙϦΰϯϞσϧʹ͸ҎԼͷ URL Ͱެ։. ਤ 2: ฏ‫ۉ‬๏ઢͷඍ෼Λ༻͍ͨҟํੑϑΟϧλϦϯάɽೖ. ͞Ε͍ͯΔσʔλΛ࢖༻ͤͯ͞௖͍ͨɽσʔλͷఏ‫ਂʹڙ‬. ࣹ͕֯ઙ͍৔߹ͷΞʔςΟϑΝΫτ͕தؒϕΫτϧΛ࢖ͬ. ँ͢Δɽ. ͨ৔߹ʹൺ΂ͯେ͖͘‫ݮ‬গ͍ͯ͠Δɽ. • F. Meinl and M. Dabrovic, URL: http://www.crytek.com/cryengine/cryengine3/downloads. ෇. ࿥. A.1 ‫ڞ‬෼ࢄߦྻϕʔεͷ GGX BRDF ϚΠΫϩϑΝηοτ BRDF[2] ͸ҎԼͷࣜͰ༩͑ΒΕΔɽ. ρ(ω i , ω o ) =. (a) ‫ڞ‬෼ࢄߦྻͷ࠷େͷ‫ݻ‬༗஋Λ (b) ό΢ϯσΟϯάϘοΫεͷ࠷ ࢖ͬͨϑΟϧλϦϯά. େ෯Λ࢖ͬͨϑΟϧλϦϯά. ਤ 3: ฏ‫ۉ‬๏ઢͷඍ෼Λ༻͍ͨ౳ํੑϑΟϧλϦϯάɽ྆ ऀͱ΋ෆշͳߴप೾ΞʔςΟϑΝΫτΛ΄΅‫׬‬શʹআ‫Ͱڈ‬ ͖Δ͕ɼա৒ͳϑΟϧλϦϯάʹΑͬͯ‫͍ڧ‬௿प೾ͷόΠ. G2 (ω i , ω o , ω m )D(ω m )F (ω m · ω o ) . 4|ω i · n||ω o · n|. ͜͜Ͱ n ͸෺ମද໘ͷ๏ઢɼω m =. ͸தؒϕ. Ϋ τ ϧ ɼD(ω m ) ͸ Ϛ Π Ϋ ϩ ϑ Ν η ο τ ͷ ๏ ઢ ෼ ෍ ؔ ਺ɼG2 (ω i , ω o , ω m ) ͸ masking-shadowing ؔ਺ɼͦͯ͠. F (ω m · ω o ) ͸ϑϨωϧ൓ࣹ߲Ͱ͋ΔɽSmith ͷ masking ؔ਺Λ G1 (ω o ) =. 1 1+Λ(ω o ). ͱ͢Δͱɼheight correlated. masking-shadowing ؔ਺͸ҎԼͷࣜͰ༩͑ΒΕΔɽ. Ξε͕ൃੜ͢Δɽ࠷େͷ‫ݻ‬༗஋Λ༻͍ͨํ͕ա৒ͳϑΟϧ λϦϯάΛ཈͑Δ͜ͱ͕ՄೳͰ͋Δɽ. ω i +ω o ||ω i +ω o ||. G2 (ω i , ω o , ω m ) =. 1 . 1 + Λ(ω i ) + Λ(ω o ). GGX ෼෍Ͱද͞ΕΔϚΠΫϩαʔϑΣε͸‫ܗ‬ঢ়ʗ৳ॖෆ. ⓒ 2016 Information Processing Society of Japan. 3.

(4) ৘ใॲཧֶձ‫ڀݚ‬ใࠂ IPSJ SIG Technical Report. Vol.2016-CG-164 No.2 2016/9/21. มʢshape/stretch invarianceʣͰ͋Γɼૈ͞ύϥϝʔλ α ͸ϚΠΫϩαʔϑΣεͷ৳ॖͷεέʔϧͰ͋Δɽͦͷͨ Ί๏ઢ෼෍ؔ਺ͱ Smith ͷ masking-shadowing ؔ਺͸෺ ମද໘ͱதؒϕΫτϧͷ৳ॖ͔Β‫ٻ‬ΊΔ͜ͱ͕Ͱ͖Δ [3]ɽ ‫ط‬ଘͷ anisotropic GGX BRDF ͸઀ઢۭؒͰͷ࣠ํ޲ʹ ϚΠΫϩαʔϑΣεΛ৳ॖͤ͞ΔϞσϧͰ͋ΔɽͦΕʹର ͠ɼ‫ڞ‬෼ࢄߦྻϕʔεͷ BRDF Ͱ͸ϚΠΫϩαʔϑΣε ͷ৳ॖํ޲͸ૈ͞ߦྻ A ͷ‫ݻ‬༗ϕΫτϧͰ͋Γɼ৳ॖͷ εέʔϧͷೋ৐͕ A ͷ‫ݻ‬༗஋Ͱ͋Δɽ͜ͷ͜ͱ͔Βɼ઀ ઢۭؒʹ͓͍ͯ ω m = [xm , ym , zm ] ͱ͢Δͱ‫ܗ‬ঢ়ෆมΑΓ ๏ઢ෼෍ؔ਺͸ҎԼͷࣜͱͳΔɽ. D(ω m ) =. 1 .  2 )2 π det(A) ([xm , ym ]A−1 [xm , ym ]T + zm. ·ͨ઀ઢۭؒʹ͓͍ͯ ω o = [xo , yo , zo ] ͱ͢Δͱɼ৳ॖෆ มΑΓɼSmith ͷ masking-shadowing ؔ਺ʹରͯ͠ҎԼͷ ͕ࣜಋग़͞ΕΔɽ.  [xo , yo ]A[xo , yo ]T + zo2 Λ(ω o ) = −0.5 + . 2|zo | ࢀߟจ‫ݙ‬ [1]. [2]. [3]. [4]. [5] [6]. [7]. [8]. Beckmann, P. and Spizzichino, A.: Scattering of Electromagnetic Waves from Rough Surfaces, MacMillan (1963). Cook, R. L. and Torrance, K. E.: A Reflectance Model for Computer Graphics, ACM Trans. Graph., Vol. 1, No. 1, pp. 7–24 (1982). Heitz, E.: Understanding the Masking-Shadowing Function in Microfacet-Based BRDFs, J. Comput. Graph. Tech., Vol. 3, No. 2, pp. 48–107 (2014). Kaplanyan, A. S., Hill, S., Patney, A. and Lefohn, A.: Filtering Distributions of Normals for Shading Antialiasing, HPG’16, pp. 151–162 (2016). Penner, E.: Shader Amortization using Pixel Quad Message Passing, GPU Pro 2, A K Peters, pp. 349–367 (2011). Saito, T. and Takahashi, T.: Comprehensible Rendering of 3-D Shapes, SIGGRAPH Comput. Graph., Vol. 24, No. 4, pp. 197–206 (1990). Trowbridge, T. S. and Reitz, K. P.: Average Irregularity Representation of a Rough Surface for Ray Reflection, J. Opt. Soc. Am, Vol. 65, No. 5, pp. 531–536 (1975). Walter, B., Marschner, S. R., Li, H. and Torrance, K. E.: Microfacet Models for Refraction Through Rough Surfaces, EGSR’07, pp. 195–206 (2007).. ⓒ 2016 Information Processing Society of Japan. 4.

(5)

参照

関連したドキュメント

From these results described above, we can conclude that the subjects grip the caps with the two-finger gripping that is easy to exert their force when the opening

In this study, the standard deviation of gray level intensity Gsa, the ratio of surface area RA, the ratio of X-direction length RLX and the one of Y

a uniform appearance, resulting in a low standard deviation. Distribution of height values is obviously varied with increasing of wrinkle, although the mean of

myocardial perfusion imaging; normal database; Japanese Society of Nuclear Medicine working group; coronary artery disease;

Finally, we give an example to show how the generalized zeta function can be applied to graphs to distinguish non-isomorphic graphs with the same Ihara-Selberg zeta

Then the strongly mixed variational-hemivariational inequality SMVHVI is strongly (resp., weakly) well posed in the generalized sense if and only if the corresponding inclusion

Test information function showed that the Short Fear of Negative Evaluation Scale had better measurement accuracy for participants with higher levels of anxiety, suggesting

Amount of Remuneration, etc. The Company does not pay to Directors who concurrently serve as Executive Officer the remuneration paid to Directors. Therefore, “Number of Persons”