Key-Lectures: Keyframes Extraction in Video Lectures

被引:9
|
作者
Kumar, Krishan [1 ,2 ]
Shrimankar, Deepti D. [2 ]
Singh, Navjot [1 ]
机构
[1] Natl Inst Technol Uttarakhand, Srinagar, Garhwal, India
[2] VNIT, Nagpur, Maharashtra, India
来源
关键词
D O I
10.1007/978-981-13-0923-6_39
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this multimedia era, the education system is going to adopt the video technologies, i.e., video lectures, e-class room, virtual classroom, etc. In order to manage the content of the audiovisual lectures, we require a huge storage space and more time to access. Such content may not be accessed in real time. In this work, we propose a novel key frame extraction technique to summarize the video lectures so that a reader can get the critical information in real time. The qualitative, as well as quantitative measurement, is done for comparing the performances of our proposed model and state-of-the-art models. Experimental results on two benchmark datasets with various duration of videos indicate that our key-lecture technique outperforms the existing previous models with the best F-measure and Recall.
引用
收藏
页码:453 / 459
页数:7
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