A Semi-Supervised Approach to Perceived Age Prediction from Face Images
スポンサーリンク
概要
- 論文の詳細を見る
We address the problem of perceived age estimation from face images, and propose a new semi-supervised approach involving two novel aspects. The first novelty is an efficient active learning strategy for reducing the cost of labeling face samples. Given a large number of unlabeled face samples, we reveal the cluster structure of the data and propose to label cluster-representative samples for covering as many clusters as possible. This simple sampling strategy allows us to boost the performance of a manifold-based semi-supervised learning method only with a relatively small number of labeled samples. The second contribution is to take the heterogeneous characteristics of human age perception into account. It is rare to misjudge the age of a 5-year-old child as 15 years old, but the age of a 35-year-old person is often misjudged as 45 years old. Thus, magnitude of the error is different depending on subjects age. We carried out a large-scale questionnaire survey for quantifying human age perception characteristics, and propose to utilize the quantified characteristics in the framework of weighted regression. Consequently, our proposed method is expressed in the form of weighted least-squares with a manifold regularizer, which is scalable to massive datasets. Through real-world age estimation experiments, we demonstrate the usefulness of the proposed method.
- （社）電子情報通信学会の論文
- 2010-10-01
著者
-
Sugiyama Masashi
Tokyo Inst. Of Technol.
-
Ueki Kazuya
Department Of Science & Engineering Waseda University:nec Soft Ltd.
-
Sugiyama Masashi
Tokyo Inst. Technol. Tokyo Jpn
-
Ueki Kazuya
Nec Soft Ltd.
-
IHARA Yasuyuki
NEC Soft, Ltd.
-
Ihara Yasuyuki
Nec Soft Ltd.
-
UEKI Kazuya
NEC Soft, Ltd.
関連論文
- Statistical active learning for efficient value function approximation in reinforcement learning (ニューロコンピューティング)
- Lighting Condition Adaptation for Perceived Age Estimation
- Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers
- Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise
- A new algorithm of non-Gaussian component analysis with radial kernel functions (Special issue: Information geometry and its applications)
- A Unified Framework of Density Ratio Estimation under Bregman Divergence
- Adaptive importance sampling with automatic model selection in value function approximation (ニューロコンピューティング)
- Fusion-Based Age-Group Classification Method Using Multiple Two-Dimensional Feature Extraction Algorithms(Pattern Recognition)
- Improving Model-based Reinforcement Learning with Multitask Learning
- Improving Model-based Reinforcement Learning with Multitask Learning
- Least-Squares Conditional Density Estimation
- Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers
- カーネル密度比推定の統計的解析(学習問題の解析,テキスト・Webマイニング,一般)
- A Semi-Supervised Approach to Perceived Age Prediction from Face Images
- Conditional Density Estimation Based on Density Ratio Estimation
- Conditional Density Estimation Based on Density Ratio Estimation
- A density ratio approach to two-sample test (パターン認識・メディア理解)
- A density ratio approach to two-sample test (情報論的学習理論と機械学習)
- Theoretical Analysis of Density Ratio Estimation
- A New Meta-Criterion for Regularized Subspace Information Criterion(Pattern Recognition)
- FOREWORD
- Superfast-Trainable Multi-Class Probabilistic Classifier by Least-Squares Posterior Fitting
- Direct Importance Estimation with Gaussian Mixture Models
- Improving the Accuracy of Least-Squares Probabilistic Classifiers
- Artist agent A[2]: stroke painterly rendering based on reinforcement learning (パターン認識・メディア理解)
- Artist agent A[2]: stroke painterly rendering based on reinforcement learning (情報論的学習理論と機械学習)
- Least-Squares Independence Test
- Density Difference Estimation
- Winning the Kaggle Algorithmic Trading Challenge with the Composition of Many Models and Feature Engineering
- Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting
- Early stopping Heuristics in Pool-Based Incremental Active Learning for Least-Squares Probabilistic Classifier
- Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifiers
- Multi-Task Approach to Reinforcement Learning for Factored-State Markov Decision Problems
- Constrained Least-Squares Density-Difference Estimation
- A Density-ratio Framework for Statistical Data Processing
- Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers
- Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation
- A Density-ratio Framework for Statistical Data Processing
- FOREWORD
- On Kernel Parameter Selection in Hilbert-Schmidt Independence Criterion