Abstract
Accurate eye localization plays a key role in many face analysis related applications. In this paper, we propose a novel eye localization framework with a group of trained filter arrays called multi-channel correlation filter bank (MCCFB). Each filter array in the bank suits to a different face condition, thus combining these filter array can locate eyes more precisely for variable poses, appearances and illuminations when comparing to single filter/filter array. To demonstrate the performance of our strategy, MCCFB is compared to other eye localization methods, experimental results show superiority of our method in detection ratio, localization accuracy and robustness.
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Yang, R., Ge, S., Xie, K., Chen, S. (2014). Eye Localization Based on Multi-Channel Correlation Filter Bank. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_33
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DOI: https://doi.org/10.1007/978-3-662-45646-0_33
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