Face tracking based on low illumination

In the environment of low illuminance, the traditional face tracking is easy to be affected by occlusion, deformation and other factors in the process of tracking, Therefore, in order to achieve accurate face tracking in low illumination environment, an improved compressed sensing tracking method combining HAAR-LBP cascade classifier is proposed in this paper. First, HAAR feature is used for face coarse tracking, then bilateral filtering is used for image enhancement, and finally LBP feature is used for fine tracking. The improved tracking method overcomes the difficulty that the traditional method has poor tracking effect and is easy to lose the target under the condition of low illuminance, and the tracking accuracy is also improved. Accroding to the experiment, it can be easily known that the accuracy of the improved algorithm is about 5% higher than that of the traditional algorithm, and the real-time performance of the improved algorithm is also improved to a certain extent.