Blurring Scene Recognition in Short Video

被引:0
|
作者
Tan, Li [1 ]
Song, Yanyan [1 ]
Dong, Xu [1 ]
Zhou, Lina [1 ]
机构
[1] Beijing Technol & Business Univ, Sch Comp & Informat Engn, Beijing, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
fuzzy recognition; deep learning; deep fusion network; scene classification; MODEL;
D O I
10.1109/siprocess.2019.8868751
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In order to solve the problems of blur and jitter in short video scenes, this paper proposes a multi-scale fusion network based on VGGNet. First, a fuzzy image data set is obtained by performing different blur processing on the clear image data set. Then, the fuzzy feature is extracted from the blurred image by using the fused depth network, and compared with the clear image extraction feature for back propagation training. Finally, the classification of fuzzy scene recognition is performed. The top3 of the Charades short video dataset has achieved 78.9% of the results, which proves that the proposed method has a good performance in blurring scene recognition.
引用
收藏
页码:75 / 78
页数:4
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