.png){kind=icon}
返回
Motion flow-based video retrieval
.png){kind=icon}
OA
AI
DOI：10.1109/TMM.2007.902875.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we propose the use of motion vectors embedded in MPEG bitstreams to generate so-called motion flows, which are applied to perform video retrieval. By using the motion vectors directly, we do not need to consider the shape of a moving object and its corresponding trajectory. Instead, we simply link the local motion vectors across consecutive video frames to form motion flows, which are then recorded and stored in a video database. In the video retrieval phase, we propose a new matching strategy to execute the video retrieval task. Motions that do not belong to the mainstream motion flows are filtered out by our proposed algorithm. The retrieval process can be triggered by query-by-sketch or query-by-example. The experiment results show that our method is indeed superb in the video retrieval process.
Keyword:
motion analysis
video retrieval
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.7
论文数:
4.5K
被引数:
2.4W
机构
暂无机构信息
引用论文
Longitudinal transcriptome analyses show robust T cell immunity during recovery from COVID-19纵向转录组分析显示新型冠状病毒肺炎恢复过程中T细胞免疫功能强大OAAI
OAAI分享收藏Self-focusing effects of dispositional self-consciousness, mirror presence, and audience presence.性格自我意识、镜像存在和观众存在的自我聚焦效应。
PREAI
分享收藏On the stability analysis of a pair of van der Pol oscillators with delayed self-connection, position and velocity couplings.png)
AIP AdvancesOAAI
AIP AdvancesIF0
OAAI分享收藏
查看更多内容