Refinement of the Shape Reconstructed by Visual Cone Intersection using Fitting the Standard Human Model

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  • HATTORI Yuichi
    Graduate School of Information Science and Technology, Osaka University
  • NAKAZAWA Atsushi
    Graduate School of Information Science and Technology, Osaka University Cybermedia Center, Osaka University
  • TAKEMURA Haruo
    Graduate School of Information Science and Technology, Osaka University Cybermedia Center, Osaka University

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  • 視体積交差法復元形状への標準人体モデル当てはめによる高精度化
  • シタイセキ コウサホウ フクゲン ケイジョウ エ ノ ヒョウジュン ジンタイ モデル アテハメ ニ ヨル コウセイドカ

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3D human model reconstruction using visual cone intersection from the images captured by multi cameras has been researched a lot, but there is a limit in the accuracy of the shape estimation because the method reconstructs from the silhouette images. Even if you increase the number of cameras to improve the accuracy, the problems, that unsmooth surfaces appear in the shape data and the normal of the surface is lost because of the characteristic of the method, will not be solved. So, in this research, we try to refine to process reshaping reconstructed shape. We estimate the posture from a captured human shape data, and create a standard human model to fit standard human model parts that was prepared beforehand. Next, we reshape and fit between human shape data and standard human model using method of alignment with reshape parameters. By this technique, we can get an accurate and refined 3D human model that maintains original human's posture and characteristic of his body.

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