Skin color detection is widely used in face detection, gesture recognition, sensitive image filtering, medical diagnosis, image enhancement and so on. It is an important technology for computer vision and image processing fields. Because human skin color is easily affected by lighting conditions, races, etc., it is difficult to achieve ideal detection results under unconstrained environments. The emergence of adaptive methods makes the above problems improved. In this paper, adaptive skin detection methods are comprehensively reviewed. The paper focuses on the analysis of adaptive skin detection methods based on parameter dynamic adjustment and high-level semantic features. Meanwhile, it discusses their respective advantages and disadvantages. On this basis, the future development trend is prospected, which aims at providing reference for related researchers.