Study on A face detection method based on elliptic skin color model

Abstract

Human face is a natural structural target with abundant details, and its detection results are easily affected by facial details, expressions and posture changes. In color images, the distribution of skin color is not affected by the changes of facial details, expression and posture, and the speed of skin color detection is very fast. This paper proposes a face detection algorithm based on elliptic skin color model. In YCbCr color space, the elliptic skin color model and logistic regression analysis were used to determine the skin color probability of each point, and the pixels of each point were mapped to [0, 1]. Based on Ostu method, a parallel genetic algorithm was used to determine the threshold of skin color segmentation to segment the face region. The results show that this method improves the speed of face detection and has good robustness to posture and expression changes.