کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
526732 869216 2016 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Recent trends in gesture recognition: how depth data has improved classical approaches *
ترجمه فارسی عنوان
روند اخیر در تشخیص ژست: چگونه داده های عمیق روش های کلاسیک بهبود یافته *
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• State of-the-art on gesture recognition approaches that exploit both RGB and depth data (RGB-D images)
• Analysis of different features
• Analysis of classification methods
• Relation between gesture complexity and features/methodologies suitability
• Comprehensive discussion and future trends of research

This paper analyzes with a new perspective the recent state of-the-art on gesture recognition approaches that exploit both RGB and depth data (RGB-D images). The most relevant papers have been analyzed to point out which features and classifiers best work with depth data, if these fundamentals are specifically designed to process RGB-D images and, above all, how depth information can improve gesture recognition beyond the limit of standard approaches based on solely color images. Papers have been deeply reviewed finding the relation between gesture complexity and features/methodologies suitability. Different types of gestures are discussed, focusing attention on the kind of datasets (public or private) used to compare results, in order to understand weather they provide a good representation of actual challenging problems, such as: gesture segmentation, idle gesture recognition, and length gesture invariance. Finally the paper discusses on the current open problems and highlights the future directions of research in the field of processing of RGB-D data for gesture recognition.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Image and Vision Computing - Volume 52, August 2016, Pages 56–72
نویسندگان
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