The invention provides a face detecting and tracking method and a device. The method comprises the steps of inputting a face image or a face video, preprocessing the face image or the face video in an illumination mode, detecting a face by usage of an Ada Boost
algorithm, confirming an initial position of the face, and tracking the face by the usage of a
Mean Shift algorithm. According to the face detecting and tracking method and the device, a self-
adaptation local
contrast enhancement method is provided to enhance image detail information in the period of image preprocessing, in order to increase robustness under different illumination conditions, face front samples under different illumination are added to training samples and accuracy of the
face detection is increased by adoption of the Ada Boost
algorithm in the period of
face detection, in order to overcome the defect that using color of the
Mean Shift algorithm is single, grads features and local binary pattern length between perpendiculars (LBP)
vein features are integrated by adoption of the
Mean Shift tracking algorithm in the period of face tracking, wherein the LBP
vein features further considers using LBP
local variance for expressing change of
image contrast information, and accuracy of the
face detection and the face tracking is improved.