کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6853614 1437210 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fourier Locally Linear Soft Constrained MACE for facial landmark localization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Fourier Locally Linear Soft Constrained MACE for facial landmark localization
چکیده انگلیسی
This paper proposes a novel nonlinear correlation filter for facial landmark localization. Firstly, we prove that SVM as a classifier can also be used for localization. Then, soft constrained Minimum Average Correlation Energy filter (soft constrained MACE) is proposed, which is more resistent to overfittings to training set than other variants of correlation filter. In order to improve the performance for the multi-mode of the targets, locally linear framework is introduced to our model, which results in Fourier Locally Linear Soft Constraint MACE (FL2 SC-MACE). Furthermore, we formulate the fast implementation and show that the time consumption in test process is independent of the number of training samples. The merits of our method include accurate localization performance, desiring generalization capability to the variance of objects, fast testing speed and insensitivity to parameter settings. We conduct the cross-set eye localization experiments on challenging FRGC, FERET and BioID datasets. Our method surpasses the state-of-arts especially in pixelwise accuracy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: CAAI Transactions on Intelligence Technology - Volume 1, Issue 3, July 2016, Pages 241-248
نویسندگان
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