Fusion of Multiple Facial Features for Age Estimation

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概要

• 論文の詳細を見る

• A novel age estimation method is presented which improves performance by fusing complementary information acquired from global and local features of the face. Two-directional two-dimensional principal component analysis ((2D)2PCA) is used for dimensionality reduction and construction of individual feature spaces. Each feature space contributes a confidence value which is calculated by Support vector machines (SVMs). The confidence values of all the facial features are then fused for final age estimation. Experimental results demonstrate that fusing multiple facial features can achieve significant accuracy gains over any single feature. Finally, we propose a fusion method that further improves accuracy.

• （社）電子情報通信学会の論文
• 2009-09-01

著者

• Lu Li

  Inst. Of Image Processing And Pattern Recognition Shanghai Jiaotong Univ.

• Lu Li

  Shanghai Jiao Tong Univ. Chn

• Lu Li

  Institute Of Image Processing And Pattern Recognition Shanghai Jiao Tong University

• SHI Pengfei

  Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University

• Shi Pengfei

  Institute Of Image Processing And Pattern Recognition Shanghai Jiao Tong University

関連論文

• Fusion of Multiple Facial Features for Age Estimation
• Sexual Dimorphism Analysis and Gender Classification in 3D Human Face
• 3D Face Landmarking Method under Pose and Expression Variations
• Fusion of multiple facial regions for expression-invariant gender classification

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