Aiming at the problem of traditional compressive tracking algorithm based on simple Haar-Like features may suffer from the tracking drift and lost when situations such as occlusion

illumination variation

deformation and background clutter occur

an improved compressive tracking algorithm based on the combination of extended Haar-Like feature and local binary pattern（LBP） feature is proposed

and applied to a particular human face tracking. Firstly

utilizing extended Haar-Like features to search for the coarse location of target

then applying LBP features to fully characterize the human face and localize the optimum position for fine tracking. Compared with the simple Haar-Like features

the LBP can construct a more stable target appearance model

and extending original Haar-Like features make the algorithm more robust in different circumstances interference and can improve the accuracy of the tracking algorithm as well. Experimental results show that the improved face compressive tracking algorithm is superior to the traditional algorithm.