کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6864787 | 1439552 | 2018 | 44 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Facial feature point detection: A comprehensive survey
ترجمه فارسی عنوان
تشخیص نقطه چهره: یک بررسی جامع
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کلمات کلیدی
یادگیری عمیق، اصلاح چهره، تشخیص نقطه ویژگی محلی سازی نقطه عطفی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
This paper presents a comprehensive survey of facial feature point detection with the assistance of abundant manually labeled images. Facial feature point detection favors many applications such as face recognition, animation, tracking, hallucination, expression analysis and 3D face modeling. Existing methods are categorized into two primary categories according to whether there is the need of a parametric shape model: parametric shape model-based methods and nonparametric shape model-based methods. Parametric shape model-based methods are further divided into two secondary classes according to their appearance models: local part model-based methods (e.g. constrained local model) and holistic model-based methods (e.g. active appearance model). Nonparametric shape model-based methods are divided into several groups according to their model construction process: exemplar-based methods, graphical model-based methods, cascaded regression-based methods, and deep learning based methods. Though significant progress has been made, facial feature point detection is still limited in its success by wild and real-world conditions: large variations across poses, expressions, illuminations, and occlusions. A comparative illustration and analysis of representative methods provides us a holistic understanding and deep insight into facial feature point detection, which also motivates us to further explore more promising future schemes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 275, 31 January 2018, Pages 50-65
Journal: Neurocomputing - Volume 275, 31 January 2018, Pages 50-65
نویسندگان
Nannan Wang, Xinbo Gao, Dacheng Tao, Heng Yang, Xuelong Li,