Key Frame Extraction in the Summary Space | |
Li, Xuelong1; Zhao, Bin2; Lu, Xiaoqiang1; Lu, XQ (reprint author), Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China. | |
刊名 | IEEE TRANSACTIONS ON CYBERNETICS |
2018-06 | |
卷号 | 48期号:6页码:1923-1934 |
关键词 | Diverse Key Frame Representative Summary Space |
ISSN号 | 2168-2267 |
DOI | 10.1109/TCYB.2017.2718579 |
产权排序 | 1 |
英文摘要 | Key frame extraction is an efficient way to create the video summary which helps users obtain a quick comprehension of the video content. Generally, the key frames should be representative of the video content, meanwhile, diverse to reduce the redundancy. Based on the assumption that the video data are near a subspace of a high-dimensional space, a new approach, named as key frame extraction in the summary space, is proposed for key frame extraction in this paper. The proposed approach aims to find the representative frames of the video and filter out similar frames from the representative frame set. First of all, the video data are mapped to a high-dimensional space, named as summary space. Then, a new representation is learned for each frame by analyzing the intrinsic structure of the summary space. Specifically, the learned representation can reflect the representativeness of the frame, and is utilized to select representative frames. Next, the perceptual hash algorithm is employed to measure the similarity of representative frames. As a result, the key frame set is obtained after filtering out similar frames from the representative frame set. Finally, the video summary is constructed by assigning the key frames in temporal order. Additionally, the ground truth, created by filtering out similar frames from human-created summaries, is utilized to evaluate the quality of the video summary. Compared with several traditional approaches, the experimental results on 80 videos from two datasets indicate the superior performance of our approach. |
学科主题 | Automation & Control Systems |
WOS研究方向 | Automation & Control Systems ; Computer Science |
语种 | 英语 |
WOS记录号 | WOS:000435342400020 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/30402] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
通讯作者 | Lu, XQ (reprint author), Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China. |
作者单位 | 1.Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning, Xian 710072, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Xuelong,Zhao, Bin,Lu, Xiaoqiang,et al. Key Frame Extraction in the Summary Space[J]. IEEE TRANSACTIONS ON CYBERNETICS,2018,48(6):1923-1934. |
APA | Li, Xuelong,Zhao, Bin,Lu, Xiaoqiang,&Lu, XQ .(2018).Key Frame Extraction in the Summary Space.IEEE TRANSACTIONS ON CYBERNETICS,48(6),1923-1934. |
MLA | Li, Xuelong,et al."Key Frame Extraction in the Summary Space".IEEE TRANSACTIONS ON CYBERNETICS 48.6(2018):1923-1934. |
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