کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4969285 | 1449928 | 2017 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Frame-wise detection of relocated I-frames in double compressed H.264 videos based on convolutional neural network
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Relocated I-frames are a key type of abnormal inter-coded frame in double compressed videos with shifted GOP structures. In this work, a frame-wise detection method of relocated I-frame is proposed based on convolutional neural network (CNN). The proposed detection framework contains a novel network architecture, which initializes with a preprocessing layer and is followed by a well-designed CNN. In the preprocessing layer, the high-frequency component extraction operation is applied to eliminate the influence of diverse video contents. To mitigate overfitting, several advanced structures, such as 1Â ÃÂ 1 convolutional filter and the global average-pooling layer, are carefully introduced in the design of the CNN architecture. Public available YUV sequences are collected to construct a dataset of double compressed videos with different coding parameters. According to the experiments, the proposed framework can achieve a more promising performance of relocated I-frame detection than a well-known CNN structure (AlexNet) and the method based on average prediction residual.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 48, October 2017, Pages 149-158
Journal: Journal of Visual Communication and Image Representation - Volume 48, October 2017, Pages 149-158
نویسندگان
Peisong He, Xinghao Jiang, Tanfeng Sun, Shilin Wang, Bin Li, Yi Dong,