کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4970376 1450123 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Pair of projections based on sparse consistence with applications to efficient face recognition
ترجمه فارسی عنوان
پویایی پیش بینی ها بر اساس تداخل پراکنده با برنامه های کاربردی برای تشخیص چهره کارآمد
کلمات کلیدی
تشخیص چهره، کاهش ابعاد، جفت پیش بینی ها، انعطاف پذیری،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Dimension reduction based feature extraction and classification method show significant performance on the high-dimensional face images. The traditional dimension reduction methods learn a projection based on the Fisher criterion or local structure of the face images. This work aims at learning a pair of projection based on sparse consistence which is measured by sparse constraint and label information for efficient face recognition. The first projection maps the original high-dimensional face images into a low-dimensional space where each face is sparse, and the second one which can also be treated as a classifier guides the sparse low-dimensional face images to the right label. The pair of projections is optimized together using alternative update rules efficiently. Due to the discriminant power of sparse face images and the supervised classifier, the proposed algorithm integrates the supervised and unsupervised information and is more efficient than them for face recognition on both learning and classifying. Experimental results on the challenging Extended Yale B, AR, and LFW face image databases demonstrate the proposed algorithm on both accuracy and efficiency.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 55, July 2017, Pages 32-40
نویسندگان
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