Nonlinear Shape-Texture Manifold Learning

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概要

• 論文の詳細を見る

• For improving the nonlinear alignment performance of Active Appearance Models (AAM), we apply a variant of the nonlinear manifold learning algorithm, Local Linear Embedded, to model shape-texture manifold. Experiments show that our method maintains a lower alignment residual to some small scale movements compared with traditional AAM based on Principal Component Analysis (PCA) and makes a successful alignment to large scale motions when PCA-AAM failed.

• （社）電子情報通信学会の論文
• 2010-07-01

著者

• MAO Xia

  School of Electronic and Information Engineering, Beihang University

• Mao Xia

  School Of Electronic And Information Engineering Beihang University

• Caleanu Catalin-daniel

  Applied Electronics Department Of University Politehnica Timisoara

• WANG Xiaokan

  School of electronic and information engineering, Beihang University

• Wang Xiaokan

  School Of Electronic And Information Engineering Beihang University

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