From coarse to fine skin and face detection

Authors:
Hichem Sahbi;Nozha Boujemaa
Affiliations:
Imedia Research Group INRIA, BP 105, F-78153, Le Chesnay, France;Imedia Research Group INRIA, BP 105, F-78153, Le Chesnay, France
Venue:
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Year:
2000

Citing 6
Cited 2

Characterization and detection of noise in clustering

Pattern Recognition Letters
Neural networks for pattern recognition

Neural networks for pattern recognition
Neural Network-Based Face Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Differential Feature Distribution Maps for Image Segmentation and Region Queries in Image Databases

CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
A Fast and Accurate Face Detector for Indexation of Face Images

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Finding faces in cluttered scenes using random labeled graph matching

ICCV '95 Proceedings of the Fifth International Conference on Computer Vision

A Hierarchy of Support Vector Machines for Pattern Detection

The Journal of Machine Learning Research
A robust incremental learning framework for accurate skin region segmentation in color images

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

A method for fine skin and face detection is described that starts from a coarse color segmentation. Some regions represents parts of human skin and are selection by minimizing an error between the color distribution of each region and the output of a compression decompression neural network, which learns skin color distribution for several populations of different ethnicity. This ANN is used to find a collection of skin regions, which is used in a second learning step to provide parameters for a Gaussian mixture model. A finer classification is performed using a Bayesian framework and makes the skin and face detection invariant to scale and lighting conditions. Finally, a face shape based model is used to decide whether a skin region is a face or not.