کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10326470 | 678070 | 2016 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Dynamic texture recognition by aggregating spatial and temporal features via ensemble SVMs
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper addresses the problem of dynamic texture recognition by aggregating spatial and temporal texture features via an ensemble SVM scheme, and bypassing the difficulties of simultaneously spatio-temporal description of DTs. More precisely, firstly, by considering a 3-dimensional DT video as a stack 2-dimensional static textures, we exploit the spatial texture features of single frame to combine different aspects of spatial structures, followed by randomly selecting several frames of the DT video in the time augmentation process. Secondly, in order to incorporate temporal information, the naive linear dynamic system (LDS) model is used to extract dynamics of DTs in temporal domain. Finally, we aggregate these spatial and temporal cues via an ensemble SVM architecture. We have experimented not only on several common dynamic texture datasets, but also on two challenging dynamic scene datasets. The results show that the proposed scheme achieves the state-of-the-art performances on the recognition of dynamic textures and dynamic scenes. Moreover, our approach offers a simple and general way to aggregate any spatial and temporal features into the task of dynamic texture recognition.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 173, Part 3, 15 January 2016, Pages 1310-1321
Journal: Neurocomputing - Volume 173, Part 3, 15 January 2016, Pages 1310-1321
نویسندگان
Feng Yang, Gui-Song Xia, Gang Liu, Liangpei Zhang, Xin Huang,