Automatic Detection of Human Nudes
International Journal of Computer Vision - 1998 Marr Prize
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
System for Screening Objectionable Images Using Daubechies' Wavelets and Color Histograms
IDMS '97 Proceedings of the 4th International Workshop on Interactive Distributed Multimedia Systems and Telecommunication Services
Skin-Color Modeling and Adaptation
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Segmenting Hands of Arbitrary Color
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
Nonstationary color tracking for vision-based human-computer interaction
IEEE Transactions on Neural Networks
An adaptive skin model and its application to objectionable image filtering
Proceedings of the 12th annual ACM international conference on Multimedia
Pattern Recognition Letters
A survey of skin-color modeling and detection methods
Pattern Recognition
AFRIGRAPH '07 Proceedings of the 5th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa
Three-Dimensional Tracking at Micro-scale Using a Single Optical Microscope
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
Segmentation of distinct homogeneous color regions in images
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
A weighted FMM neural network and its application to face detection
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Robust real-time face detection using hybrid neural networks
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Skin detection in videos in the spatial-range domain
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
A fast real-time skin detector for video sequences
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Computational strategies for skin detection
CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging
Detecting Facial Expressions for Monitoring Patterns of Emotional Behavior
International Journal of Monitoring and Surveillance Technologies Research
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Due to variations of lighting conditions, camera hardware settings, and the range of skin coloration among human beings, a pre-defined skin-color model cannot accurately capture the wide distribution of skin colors in individual images. In this paper, we propose an adaptive skin-detection method, which allows modeling true skincolor distribution with significantly higher accuracy and flexibility than other methods attain. In principle, the proposed method follows a two-step process. For a given image, we first perform a rough skin classification using a generic skin model which defines the Skin-Similar space. In the second step, a Gaussian Mixture Model (GMM), specific to the image under consideration and refined from the Skin-Similar space, is derived using the standard Expectation-Maximization (EM) algorithm. Then, we use an SVM (Support Vector Machine) classifier to identify the skin Gaussian from the trained GMM (which contains two Gaussian components) by incorporating spatial and shape information of the skin pixels. This adaptive method can be applied to both still images and video applications. Results of extensive experiments performed on live video sequences and large image databases have demonstrated the effectiveness and benefits of the proposed model.