کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4947699 1439588 2017 29 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Locality-constrained linear coding based bi-layer model for multi-view facial expression recognition
ترجمه فارسی عنوان
مدل دو لایه مبتنی بر کدگذاری خطی محدوده محلی برای تشخیص بیان چندگانه
کلمات کلیدی
به رسمیت شناختن صورت چند نمایه، مدل دو لایه مبتنی بر کدگذاری مبتنی بر محدوده محلی، کیف از ویژگی های،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Multi-view facial expression recognition is a challenging and active research area in computer vision. In this paper, we propose a simple yet effective method, called the locality-constrained linear coding based bi-layer (LLCBL) model, to learn discriminative representation for multi-view facial expression recognition. To address the issue of large pose variations, locality-constrained linear coding is adopted to construct an overall bag-of-features model, which is then used to extract overall features as well as estimate poses in the first layer. In the second layer, we establish one specific view-dependent model for each view, respectively. After the pose information of the facial image is known, we use the corresponding view-dependent model in the second layer to further extract features. By combining all the features in these two layers, we obtain a unified representation of the image. To evaluate the proposed approach, we conduct extensive experiments on both BU-3DFE and Multi-PIE databases. Experimental results show that our approach outperforms the state-of-the-art methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 239, 24 May 2017, Pages 143-152
نویسندگان
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