Study on Illumination Insensitive Face Detection Based on Normalization Techniques
スポンサーリンク
概要
- 論文の詳細を見る
Face detection has been attracting much academic attention. Illumination problem is one of the most important aspects that decreases its performance. Conventional methods have focused on extracting illumination invariant features or utilizing skin color information. However, the features and colors are unreliable in adverse lighting conditions. In this paper, we investigate various illumination normalization techniques for learning-based face detection under varying illumination. They are four illumination insensitive face representation techniques and five histogram-based normalization methods including our proposed method SH (segmentation-based HHTS). The experimental results show that 1) effective illumination normalization techniques in face recognition are not necessarily useful in face detection; 2) histogram-based methods significantly outperform illumination insensitive face representation techniques in average; 3) SH obtains the best results.
- 一般社団法人電子情報通信学会の論文
- 2013-08-26
著者
-
Nagahashi Hiroshi
Imaging Science And Engineering Laboratory Tokyo Institute Of Technology
-
YAO Min
Department of Information Processing, Tokyo Insitute of Technology
関連論文
- Structural Evolution of Neural Networks Having Arbitrary Connections by a Genetic Method
- A New Method for Smooth Interpolation without Twist Constraints
- DISTANCE MEASUREMENT OF A REAL-WORLD ENVIRONMENT USING AN ACTIVE CAMERA SYSTEM(International Workshop on Advanced Image Technology 2006)
- Interpolation of CT Slices for Laser Stereolithography
- Orientable Closed Surface Construction from Volume Data
- A Method for Watermarking to Bezier Polynomial Surface Models (Computer Graphics)
- Texture Classification Using Hierarchical Linear Discriminant Space(Image Recognition, Computer Vision)
- Parallel Computation of Parametric Piecewise Modeling Method
- Texture-based Real-time Vision System for Detection of Automobile Cylinder Sleeves
- D-12-43 Photograph Based Pair-matching Recognition of Human Faces
- D-12-61 The pedestrian Tracking Based on an On-line Boosting Method
- Verification of physical properties of materials modeled with mass-spring systems (マルチメディア・仮想環境基礎)
- Verification of physical properties of materials modeled with mass-spring systems (画像工学)
- D-16-5 Multifractal Analysis for HCC Biopsy Images
- Classification of Prostate Histopathology Images Based on Multifractal Analysis
- D-12-22 A Simple Approach Tackling Illumination Problem of Face Detection
- Study on Illumination Insensitive Face Detection Based on Normalization Techniques