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Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 4, Pages 1,493-1,515, DOI: https://doi.org/10.21307/ijssis-2017-717
License : (CC BY-NC-ND 4.0)
Received Date : 03-July-2014 / Accepted: 15-October-2014 / Published Online: 01-December-2014
In the information era, the technology of biological character recognition 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 semi-active 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 semiactive
appearance model is proposed, which has a simple calculation and higher accuracy of face
alignment. Finally, experiments were designed to demonstrate the effectiveness of the proposed
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