Knowledge Commons of Institute of Automation，CAS
| Spatiotemporal Grid Flow for Video Retargeting | |
Li, Bing1,2 ; Duan, Ling-Yu2; Wang, Jinqiao3; Ji, Rongrong2; Lin, Chia-Wen4; Gao, Wen2
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| 发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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| 2014-04-01 | |
| 卷号 | 23期号:4页码:1615-1628 |
| 文章类型 | Article |
| 摘要 | Video retargeting is a useful technique to adapt a video to a desired display resolution. It aims to preserve the information contained in the original video and the shapes of salient objects while maintaining the temporal coherence of contents in the video. Existing video retargeting schemes achieve temporal coherence via constraining each region/pixel to be deformed consistently with its corresponding region/pixel in neighboring frames. However, these methods often distort the shapes of salient objects, since they do not ensure the content consistency for regions/pixels constrained to be coherently deformed along time axis. In this paper, we propose a video retargeting scheme to simultaneously meet the two requirements. Our method first segments a video clip into spatiotemporal grids called grid flows, where the consistency of the content associated with a grid flow is maintained while retargeting the grid flow. After that, due to the coarse granularity of grid, there still may exist content inconsistency in some grid flows. We exploit the temporal redundancy in a grid flow to avoid that the grids with inconsistent content be incorrectly constrained to be coherently deformed. In particular, we use grid flows to select a set of key-frames which summarize a video clip, and resize subgrid-flows in these key-frames. We then resize the remaining nonkey-frames by simply interpolating their grid contents from the two nearest retargeted key-frames. With the key-frame-based scheme, we only need to solve a small-scale quadratic programming problem to resize subgrid-flows and perform grid interpolation, leading to low computation and memory costs. The experimental results demonstrate the superior performance of our scheme. |
| 关键词 | Video Retargeting Video Warping Dynamic Programming Quadratic Programming |
| WOS标题词 | Science & Technology ; Technology |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000332123900005 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/3343 |
| 专题 | 紫东太初大模型研究中心_图像与视频分析 |
| 通讯作者 | Wang, Jinqiao |
| 作者单位 | 1.Univ Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Peking Univ, Sch Elect & Engn Comp Sci, Inst Digital Media, Beijing 100871, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 4.Natl Tsing Hua Univ, Hsinchu 30013, Taiwan |
| 通讯作者单位 | 模式识别国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Li, Bing,Duan, Ling-Yu,Wang, Jinqiao,et al. Spatiotemporal Grid Flow for Video Retargeting[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2014,23(4):1615-1628. |
| APA | Li, Bing,Duan, Ling-Yu,Wang, Jinqiao,Ji, Rongrong,Lin, Chia-Wen,&Gao, Wen.(2014).Spatiotemporal Grid Flow for Video Retargeting.IEEE TRANSACTIONS ON IMAGE PROCESSING,23(4),1615-1628. |
| MLA | Li, Bing,et al."Spatiotemporal Grid Flow for Video Retargeting".IEEE TRANSACTIONS ON IMAGE PROCESSING 23.4(2014):1615-1628. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Spatiotemporal grid （3766KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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