In the information era, the technology of biological characterrecognition has attracted more and more attentions. In this paper, by investigating theories of active appearance model and inverse compositional image alignment algorithm, we mainly proposed a semiactive appearance model for face alignment based on improving the classical models in the aspects of computation complexity, easily suffering from light, angle and expression, and so on. Firstly, the model of active appearance and the algorithm of alignment are investigated. For the inefficiency of classic gradient descent method in the matching process, the inverse compositional image alignment algorithm is proposed. Then, through combining the active appearance model and Grey Level Co-occurrence Matrix, a novel semi-active appearance model is proposed, which has an simple calculation and higheraccuracy of identification. Finally, experiments were designed to demonstrate the effectiveness of the proposed algorithms.