کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969813 1449984 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Joint representation classification for collective face recognition
ترجمه فارسی عنوان
طبقه بندی نمایندگی مشترک برای تشخیص چهره جمعی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
In recent years, many representation based classifications have been proposed and widely used in face recognition. However, these methods code and classify testing images separately even for image-set of the same subject. This scheme utilizes only an individual representation rather than the collective one to classify such a set of images, doing so obviously ignores the correlation among the given set of images. In this paper, a joint representation classification (JRC) for collective face recognition is presented. JRC takes the correlation of multiple images as well as a single representation into account. Even for an image-set mixed with different subjects, JRC codes all the testing images over the base images simultaneously to facilitate recognition. To this end, the testing images are aligned into a matrix and the joint representation coding is formulated as a generalized l2,q−l2,p matrix minimization problem. A unified algorithm, named by iterative quadratic method (IQM), and its practical implementation are developed specially to solve the induced optimization problem for any q∈[1,2] and p∈(0,2]. Experimental results on three public databases show that the JRC with practical IQM not only saves much computational cost but also achieves better performance in collective face recognition than state-of-the-art methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 63, March 2017, Pages 182-192
نویسندگان
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