Towards Distributed Video Summarization

被引:4
|
作者
Chakraborty, Shayok [1 ]
Tickoo, Omesh [2 ]
Iyer, Ravishankar [2 ]
机构
[1] Carnegie Mellon Univ, Elect & Comp Engn, Pittsburgh, PA 15213 USA
[2] Intel Labs, Hillsboro, OR USA
来源
MM'15: PROCEEDINGS OF THE 2015 ACM MULTIMEDIA CONFERENCE | 2015年
关键词
Video Summarization; Submodular Functions;
D O I
10.1145/2733373.2806355
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Video summarization is a fertile topic in multimedia research. While the advent of modern video cameras and several social networking and video sharing websites (like YouTube, Flickr, Facebook) has led to the generation of humongous amounts of redundant video data, video summarization has emerged as an effective methodology to automatically extract a succinct and condensed representation of a given video. The unprecedented increase in the volume of video data necessitates the usage of multiple, independent computers for its storage and processing. In order to understand the overall essence of a video, it is therefore necessary to develop an algorithm which can summarize a video distributed across multiple computers. In this paper, we propose a novel algorithm for distributed video summarization. Our algorithm requires minimal communication among the computers (over which the video is stored) and also enjoys nice theoretical properties. Our empirical results on several challenging, unconstrained videos corroborate the potential of the proposed framework for real-world distributed video summarization applications.
引用
收藏
页码:883 / 886
页数:4
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