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Volumn 17, Issue 3-4, 2006, Pages 229-237

Key-styling: Learning motion style for real-time synthesis of 3D animation

Author keywords

Motion capture data; Motion synthesis; Neural networks; Self organizing mixture network

Indexed keywords

KEY-STYLING; MOTION CAPTURE DATA; MOTION SYNTHESIS; SELF-ORGANIZING MIXTURE NETWORK;

EID: 33745835071     PISSN: 15464261     EISSN: 1546427X     Source Type: Journal    
DOI: 10.1002/cav.126     Document Type: Conference Paper
Times cited : (9)

References (12)
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    • 0035272084 scopus 로고    scopus 로고
    • Self-organizing mixture networks for probability density estimation
    • Yin H-J, Allinson NM. Self-organizing mixture networks for probability density estimation. IEEE Transactions on Neural Networks 2001; 12(2): 405-411.
    • (2001) IEEE Transactions on Neural Networks , vol.12 , Issue.2 , pp. 405-411
    • Yin, H.-J.1    Allinson, N.M.2
  • 2
    • 77953859307 scopus 로고    scopus 로고
    • Motion texture: A two-level statistical model for character motion synthesis
    • Li Y, Wang T-S, Shum H-Y. Motion texture: a two-level statistical model for character motion synthesis. Proceedings of ACM SIGGRAPH, pages 465-472, 2002.
    • (2002) Proceedings of ACM SIGGRAPH , pp. 465-472
    • Li, Y.1    Wang, T.-S.2    Shum, H.-Y.3
  • 6
    • 0041455573 scopus 로고
    • The theory of segmental hidden Markov models
    • Cambridge Univ. Eng. Dept.
    • Gales MJF, Young SJ. The theory of segmental hidden Markov models. Technical report, Cambridge Univ. Eng. Dept., 1993.
    • (1993) Technical Report
    • Gales, M.J.F.1    Young, S.J.2
  • 7
    • 84898980901 scopus 로고    scopus 로고
    • Gaussian process latent variable models for visualisation of high dimensional data
    • Lawrence ND. Gaussian process latent variable models for visualisation of high dimensional data. In Proc. 16th NIPS, 2004.
    • (2004) Proc. 16th NIPS
    • Lawrence, N.D.1
  • 9
    • 0005009033 scopus 로고    scopus 로고
    • Pattern discovery via entropy minimization
    • Heckerman D, Whittaker C (eds). Morgan Kaufmann, Los Altos
    • Brand M. Pattern discovery via entropy minimization. In Artificial Intelligence and Statistics, vol. 7. Heckerman D, Whittaker C (eds). Morgan Kaufmann, Los Altos, 1999.
    • (1999) Artificial Intelligence and Statistics , vol.7
    • Brand, M.1
  • 11
    • 0032122727 scopus 로고    scopus 로고
    • Averaging, maximum penalised likelihood and bayesian estimation for improving gaussian mixture probability density estimates
    • Ormoneit D, Tresp V. Averaging, maximum penalised likelihood and bayesian estimation for improving gaussian mixture probability density estimates. IEEE Transactions on Neural Networks 1998; 9: 639-650.
    • (1998) IEEE Transactions on Neural Networks , vol.9 , pp. 639-650
    • Ormoneit, D.1    Tresp, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.