[2][3][4][5] 4 ( 1 ) ( 2 ) ( 3 ) ( 4 ) 2. Shiratori [2] Shiratori [3] [4] GP [5] [6] [7] [8][9] Kinect Choi [10] 3. 1 c 2016 Information Processing So

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1,a) 2 2 1 2,b) 3,c) A choreographic authoring system reflecting a user s preference Ryo Kakitsuka 1,a) Kosetsu Tsukuda 2 Satoru Fukayama 2 Naoya Iwamoto 1 Masataka Goto 2,b) Shigeo Morishima 3,c) Abstract: We propose a new system for constructing character dance animation by considering animator s preferences. First, a user of the proposed system assigns a preferred motion, obtained through a searching algorithm, to arbitrary part in the music. Then the proposed system automatically assigns motions to the other remaining parts of the music by using motions in a database. This system enables a user to create a new dance performance for character animation considering his/her preference. Keywords: relevance feedback, character animation, motion capture, dance 1. 3DCG 1 Waseda University 2 National Institute of Advanced Industrial Science and Technology (AIST) 3 Waseda Research Institute for Science and Engineering a) kakitsuka.99821@ruri.waseda.jp b) m.goto@aist.go.jp c) shigeo@waseda.jp web *1 N [1] web *1 http://www.nicovideo.jp c 2016 Information Processing Society of Japan 1

[2][3][4][5] 4 ( 1 ) ( 2 ) ( 3 ) ( 4 ) 2. Shiratori [2] Shiratori [3] [4] GP [5] [6] [7] [8][9] Kinect Choi [10] 3. 1 c 2016 Information Processing Society of Japan 2

[12] Dou [13] n + 1 m n+1 1. 1 1 1 2 1 3 1 4 1 5 1 3.1 3.2 [11] 4 3.1 m n+1 = argmax m U\S n {ρ rel(q, m)+(1 ρ) Φ(m, S n, L l )} (1) rel(q, m) Φ(m, S n, L l ) m 0 ρ 1 (1) rel(q, m) q m RMS W (f) = N i=1 α i x i (2) N x i α i (1) Φ(m, S n, L l ) Φ(m, S n, L l ) =τ min{d(m, m i ) m i S n } + (1 τ) max{sim(m, m j ) m j L l } (3) S n n L l D(m, m i ) Sim(m, m i ) m m i [8] (1) U m n+1 n S n τ c 2016 Information Processing Society of Japan 3

k τ τ k = 19 20 τ k 1 (4) τ 0 = 1 3.2 3.2.1 S C(= 1/S) C [14] 2 S S pose S move A i A B j B S pose S move S pose v β l v h S pose (i A, j B ) = N β l (h(v l (i A )) h(v l (j B ))) (5) l S move h v (v l (j B ) v l (i A )) S move (i A, j B ) = N l g[x] = β l g[h(v l (j B ) v l (i A )) h( v l (i A ))] g[h(v l (j B ) v l (i A )) h( v l (j B ))] { x if x > 0 0 otherwise (6) (7) 2. S = S pose + S move (8) 3.2.2 5 5 3.3 3 1 3 3 3.1 Set Search Generate 4. 4.1 c 2016 Information Processing Society of Japan 4

3. 6 1 15 5 6 i=1 j=i+1 D(m i, m j ) (9) 4 4 3 (1) 4. 5. 5. 3D 4.2 4 4 5 3D 3D Lat JST CREST OngaCREST c 2016 Information Processing Society of Japan 5

[1] CGM :,, : 5. : N Fluxonomy ( ) Vol. 53, No. 5, pp. 489 494 (2012). [2] Shiratori, T., Nakazawa, A. and Ikeuchi, K.: Dancing-to- Music Character Animation, Computer Graphics Forum, Vol. 25, No. 3, Wiley Online Library, pp. 449 458 (2006). [3] Ofli, F., Erzin, E., Yemez, Y. and Tekalp, A. M.: Learn2dance: Learning statistical music-to-dance mappings for choreography synthesis, IEEE Transactions on Multimedia, Vol. 14, No. 3, pp. 747 759 (2012). [4] Oore, S. and Akiyama, Y.: Learning to synthesize arm motion to music by example (2006). [5] Fukayama, S. and Goto, M.: Automated choreography synthesis using a Gaussian process leveraging consumergenerated dance motions, Proceedings of the 11th Conference on Advances in Computer Entertainment Technology, ACM, p. 23 (2014). [6] (SLP) Vol. 2012, No. 25, pp. 1 6 (2012). [7] Mukai, T. and Kuriyama, S.: Pose-timeline for propagating motion edits, Proceedings of the 2009 ACM SIG- GRAPH/Eurographics Symposium on Computer Animation, ACM, pp. 113 122 (2009). [8] Wang, P., Lau, R. W., Pan, Z., Wang, J. and Song, H.: An Eigen-based motion retrieval method for real-time animation, Computers & Graphics, Vol. 38, pp. 255 267 (2014). [9] Raptis, M., Kirovski, D. and Hoppe, H.: Real-time classification of dance gestures from skeleton animation, Proceedings of the 2011 ACM SIGGRAPH/Eurographics symposium on computer animation, ACM, pp. 147 156 (2011). [10] Choi, M. G., Yang, K., Igarashi, T., Mitani, J. and Lee, J.: Retrieval and visualization of human motion data via stick figures, Computer Graphics Forum, Vol. 31, No. 7, Wiley Online Library, pp. 2057 2065 (2012). [11] Perfume: Perfume GLOBAL SITE, http://www.perfume-global.com/ (2012). [12] Rocchio, J. J.: Relevance feedback in information retrieval (1971). [13] Dou, Z., Hu, S., Chen, K., Song, R. and Wen, J.-R.: Multi-dimensional search result diversification, Proceedings of the fourth ACM international conference on Web search and data mining, ACM, pp. 475 484 (2011). [14] Dijkstra, E. W.: A note on two problems in connexion with graphs, Numerische mathematik, Vol. 1, No. 1, pp. 269 271 (1959). c 2016 Information Processing Society of Japan 6