Abstract
We present a coarsely locating little points and finely locating many points approach for face alignment. This cascade structure replies to 2 problems existing all the time in face alignment: the initialization and great accuracy difference between inner points and outline points. First, we adopt DCNN to coarsely localize 5 points: two pupils, nose and two mouth corners. Second, based on shape initialization of coarse location, using SDM with extracting simplified SIFT features, we finely localizes 49 inner points and 17 outline points. Experiments on CAS-PEAL-R1 and FERET database show that our approach is accurate and robust. The proposed method achieves 99.23% localization accuracy of eyes on CAS-PEAL-R1.
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Tang, Q., Zhang, Q., Zhang, X., Cai, Z., Zhang, X. (2015). A DCNN and SDM Based Face Alignment Algorithm. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_12
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DOI: https://doi.org/10.1007/978-3-319-25417-3_12
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