Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
Statistical color models with application to skin detection
International Journal of Computer Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Locating Facial Region of a Head-and-Shoulders Color Image
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
ACM SIGGRAPH 2004 Papers
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skin Detection: A Bayesian Network Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Mixture Clustering Using Multidimensional Histograms for Skin Detection
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Skin Segmentation Using Color Pixel Classification: Analysis and Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of skin-color modeling and detection methods
Pattern Recognition
Naked image detection based on adaptive and extensible skin color model
Pattern Recognition
Selection and Fusion of Color Models for Image Feature Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
An adaptive multiple model approach for fast content-based skin detection in on-line videos
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
Skin Paths for Contextual Flagging Adult Videos
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Steerable semi-automatic segmentation of textured images
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Automatic image segmentation by positioning a seed
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Systematic skin segmentation: merging spatial and non-spatial data
Multimedia Tools and Applications
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We present a principled approach for general skin segmentation using graph cuts. We present the idea of a highly adaptive universal seed thereby exploiting the positive training data only. We model the skin segmentation as a min-cut problem on a graph defined by the image color characteristics. The prior graph cuts based approaches for skin segmentation do not provide general skin detection when the information of foreground or background seeds is not available. We propose a concept for processing arbitrary images; using a universal seed to overcome the potential lack of successful seed detections thereby providing basis for general skin segmentation. The advantage of the proposed approach is that it is based on skin sampled training data only making it robust to unseen backgrounds. It exploits the spatial relationship among the neighboring skin pixels providing more accurate and stable skin blobs. Extensive evaluation on a dataset of 8991 images with annotated pixel-level ground truth show that the universal seed approach outperforms other state of the art approaches.