ShadowingPlane_CamereReady.dvi
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1 Fast Shading and Shadowing of Virtual Obects Using Shadowing Planes in Mixed Reality y yy yy Tetsuya Kakuta y,takeshi Oishi yy and Katsushi Ikeuchi yy Abstract We have developed a fast shading and shadowing method that uses the shadowing planes and the images in mixed reality (MR). The method is model-based and computable in real time by using a standard graphics processing unit (GPU) making it particularly effective when used with an outdoor MR application. To express the shadows of obects, we map the shadow images that are synthesized from the images rendered offline with the lights onto the shadowing planes, and we compute alpha blending with the obects. The shadowing planes are generated from convex hulls of obects. We obtain the radiance parameters of the real scene from an omnidirectional image and compute the linear sum of the radiance parameters and the images on the GPU. We applied this shadowing method to both an indoor and outdoor MR application and found it to be effective. 1. CG MR: Mixed Reality 1)3) MR HMD CG CG MR MR 4) Shade y DC TEL yy TEL y Graduate School of Interdisciplinary Information Studies, The University oftokyo, JSPS Researc Fellow (7 3 1, Hongo, Bunkyo-ku, Tokyo , Japan) yy Interfaculty Initiative in Information Studies, The University of Tokyo (7 3 1, Hongo, Bunkyo-ku, Tokyo , Japan) Shadow CG 5)7) MR CG MR 8) 9) 10) 11) 12) 13) 14) 15) 16) 11) 9) 17) Vol. 62, No. 5, pp. 18 (2008) (1) 1
2 1 Shadowing using shadowing planes. MR 3 ffl ffl GPU 1 9) 17) GPU 2 3 GPU a 3D b c 2 Flowchart of the proposed method. d e f GPU g h D 1 MR 2 (2) Vol. 62, No. 5 (2008)
3 4 Offset of shadowing plane. 14) 3 Generation of shadowing planes ) 19) 3b 3D 3c Z-fighting Z Z OpenGL Z near nfar f Z Z ob Z Z ndc 2fn Z ndc = + f + n (1) (f n)z ob f n near 0far 1 Z ob d d = Z ndc fn = + f + n (f n)z ob 2(f n) (2) (3) 3 OpenGL glpolygonoffset 3. 4 E P shadow E 0 E 0 P I P d 10) P I E 0 = E P (4) d I shadow P I P d I shadow =1 (5) (3) 3
4 ΣI shadow I Σd shadow I P shadow S 1 I,1 S 2 I,2 S n d,1 S 1 d,1 S 2 d,1 S n ΣI Σd 6 Linear combination of luminance parameters and images and diffuse components. 0 i 5 Generation of shadow images and mapping onto shadowing planes. 5 I shadow a 5b P shadow I shadow 0 E 0 E 0 = E(1 I shadow )+P shadow I shadow (6) 6 P shadow 0 P shadow I shadow =0 E 0 = E(1 I shadow ) (7) GPU m P shadow f = 1; 2;:::;mg n L i fi = 1; 2;:::;ng P shadow I ;i P shadow d ;i v S 1 S 2 S 3 S 4 u S n-3 S n-2 S n-1 S n 7 Synthesis of images using fragment shader. S i 6a P shadow I ;i S i P I 6 b d ;i P d 7 GPU L i m d ;i S i UV 4 (4) Vol. 62, No. 5 (2008)
5 N L d A B S i d 8 Hemispheric surface light source. 10 Estimation of light distribution from omnidirectional image. N Geodesic Dome i Li i P shadow I,i n 9 Generation of images. 11 MR Apparance of MR-system A A A ffi L( ; ffi) A ( ; ffi) (d ; dffi) B A E 20) E = Z ß Z ß ß 0 2 L( ; ffi)sin cos d dffi (8) 21) Geodesic Dome Geodesic Dome 3 22) 23) 9a Geodesic Dome L i A E L i P shadow Geodesic Dome L i I ;i d ;i Geodesic Dome L i 2550:0 ο 1:0 S i MR (5) 5
6 GPU RGBA 5. 1 MR MR MR Platform 24) MR Platform HMDPolhemus 6 FASTRAK HMD FIT FI-19 CCD Victor KY-57 PC OS: Windows XPSP2CPU: Core2Duo E GHzRAM: 4GBGPU: nvidia GeForce8800GTS 640MB MR a 12b 12c 12d a 13b MR 5m b % VRMR CG 25) 26) : 13c 22% 6. MR 1 2 GPU Geodesic Dome 6 (6) Vol. 62, No. 5 (2008)
7 12 Comparison of shading and shadowing of virtual obect indoors. 13 Comparison of shading and shadowing of virtual obect outdoors pp (March 1997) 2R. Azuma ASurvey of Augmented Reality Presence: Teleoperators and Virtual Environments64pp (August 1997) 3R. AzumaY. BaillotR. BehringerS. FeinerS. Julierand B. MacIntyre Recent Advances in Augmented Reality IEEE Computer Graphics and Applications216, pp (November 2001) 4 44pp (December 1999) 5A. WooP. Poulinand A. Fournier A Survey of Shadow Algorithms IEEE Computer Graphics and Applications106 pp (November 1990) 6F. Crow Shadow Algorithms for Computer Graphics Proc. SIGGRAPH'77pp (1977) 7J. M. HasenfratzM. LapierreN. Holzschuchand F.X. Sillion ASurvey of Real-time Soft Shadows Algorithms Computer Graphics Forumpp (December 2003) 8K. Jacobs and C. Loscos Classification of Illumination Methods for Mixed Reality Proc. Eurographics State of the Art Report(STAR)pp (September 2004) 9 D-IIJ-84-D-II (August 2001) 10I. SatoY. Satoand K. IkeuchiAcquiring a Radiance Distribution to Superimpose Virtual Obects onto a Real Scene IEEE Trans. on Visualization and Computer Graphics51pp.1-12 (January-March 1999) 11P. Debevec Rendering Synthetic Obects into Real Scenes: Bridging Traditional and Image-Based Graphics with Global Ilumination and High Dynamic Range Photography Proc. SIG- GRAPH '98pp (July 1998) 12M. Kanbara and N. Yokoya Geometric and photometric registration for real-time augmented reality Proc. Int. Symp. on Mixed and Augmented Reality (ISMAR02)pp (September 2002) 13H. MatsuokaA. Onozawa and E. HosoyaEnvironment Mapping for Obects in the Real World: a Trial Using ARToolkit Proc. Int. Augmented Reality Toolkit Workshop (September 2002) 14I. SatoY. Sato and K. Ikeuchi Illumination from Shadows IEEE Trans. on Pattern Analysis and Machine Intelligence25 3pp (March 2003) 15M. HallerS. Drab and W. Hartmann A Real-Time Shadow Approach for an Augmented Reality Application Using Shadow Volumes Proc. Symp. on ACM Virtual Reality Software and Technology(VRST'03)pp (October 2003) 16 MIRU2005pp (July 2005) 17J. S. NimeroffE. Simoncelli and J. Dorsey Efficient Re- (7) 7
8 Rendering of Naturally Illuminated Environments Proc. Eurographics Workshop on Rendering (EGWR94)pp (June 1994) 18M. LevoyK. PulliB. CurlessS. RusinkiewiczD. KollerL. PereiraM. GinztonS. AndersonJ. DavisJ. GinsbergJ. Shadeand D. FulkThe Digital Michelangelo Proect: 3D Scanning of Large Statues Proc. SIGGRAPH'00pp (July 2000) 19K. Ikeuchi Modeling from Reality Proc. Third International Conference on 3D Digital Imaging and Modeling (3DIM'01) pp.177 (May 2001) 20B. K. P. Horn Robot Vision The MIT Press (March 1986) 21P. P. SloanJ. KautzJ. SnyderPrecomputed Radiance Transfer for Real-Time Rendering in Dynamic, Low-Frequency Lighting Environments Proc. SIGGRAPH'02pp (July 2002) 22A. Pugh Polyhedra: a Visual Approach University of California Press (September 1976) 23K. IkeuchiRecognition of 3D Obect using the Extended Gaussian Image Proc. 7th International Joint Conference on Artificial Intelligencepp (August 1981) 24S. UchiyamaK. TakemotoK. SatohH. Yamamotoand H. Tamura MR Platform: A Basic Body on Which Mixed Reality Applications Are Built Proc. Int. Symp. on Mixed and Augmented Reality (ISMAR02)pp (September 2002) pp.263 (March 1995) pp.169 (March 2007) DC MIT CMU (8) Vol. 62, No. 5 (2008)
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(a) 1 (b) 3. Gilbert Pernicka[2] Treibitz Schechner[3] Narasimhan [4] Kim [5] Nayar [6] [7][8][9] 2. X X X [10] [11] L L t L s L = L t + L s
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![1 Kinect for Windows M = [X Y Z] T M = [X Y Z ] T f (u,v) w 3.2 [11] [7] u = f X +u Z 0 δ u (X,Y,Z ) (5) v = f Y Z +v 0 δ v (X,Y,Z ) (6) w = Z +](/thumbs/81/83701592.jpg "1 Kinect for Windows M = [X Y Z] T M = [X Y Z ] T f (u,v) w 3.2 [11] [7] u = f X +u Z 0 δ u (X,Y,Z ) (5) v = f Y Z +v 0 δ v (X,Y,Z ) (6) w = Z +")
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4. C i k = 2 k-means C 1 i, C 2 i 5. C i x i p [ f(θ i ; x) = (2π) p 2 Vi 1 2 exp (x µ ] i) t V 1 i (x µ i ) 2 BIC BIC = 2 log L( ˆθ i ; x i C i ) + q
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x-means 1 2 2 x-means, x-means k-means Bayesian Information Criterion BIC Watershed x-means Moving Object Extraction Using the Number of Clusters Determined by X-means Clustering Naoki Kubo, 1 Kousuke
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Research of improving of recognition ability in Face recognition system Abstract The age when baiometrics was used as a password came today. Because various baiometrics such as a voice, a fingerprint,
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17 Proposal of an Algorithm of Image Extraction and Research on Improvement of a Man-machine Interface of Food Intake Measuring System
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Vol.54 No.7 1937 1950 (July 2013) 1,a) 2012 11 1, 2013 4 5 1 Similar Sounds Sentences Generator Based on Morphological Analysis Manner and Low Class Words Masaaki Kanakubo 1,a) Received: November 1, 2012,
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1 1 2 1 Estimation of Shielding Object Distribution in Scattering Media by Analyzing Light Transport Shosei Moriguchi, 1 Yasuhiro Mukaigawa, 1 Yasuyuki Matsushita 2 and Yasushi Yagi 1 In this paper, we
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A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member
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14 2 5 i ii Surface Reconstruction from Point Cloud of Human Body in Arbitrary Postures Isao MORO Abstract We propose a method for surface reconstruction from point cloud of human body in arbitrary postures.
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H.264 CABAC 1 1 1 1 1 2, CABAC(Context-based Adaptive Binary Arithmetic Coding) H.264, CABAC, A Parallelization Technology of H.264 CABAC For Real Time Encoder of Moving Picture YUSUKE YATABE 1 HIRONORI
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1, 2 1 1 1 Instrument Separation in Reverberant Environments Using Crystal Microphone Arrays Nobutaka ITO, 1, 2 Yu KITANO, 1 Nobutaka ONO 1 and Shigeki SAGAYAMA 1 This paper deals with instrument separation
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1 1 1 Posture Esimation by Using 2-D Fourier Transform Yuya Ono, 1 Yoshio Iwai 1 and Hiroshi Ishiguro 1 Recently, research fields of augmented reality and robot navigation are actively investigated. Estimating
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