STAR:一个基于内容的视频检索系统,用于移动摄像机视频拍摄

C. Chattopadhyay, Sukhendu Das
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引用次数: 11

摘要

提出了一种基于无监督内容的视频检索(CBVR)系统STAR (spatial - temporal Analysis and Retrieval)的设计。STAR的关键洞察力和主要贡献在于,它使用联合时空特征表示对视频内容进行建模,并从数据库中检索具有相似运动对象和运动轨迹的视频。从移动摄像机的视频镜头中提取前景移动斑点,并结合轨迹进行摄像机运动补偿,形成时空体(STV)。对STV进行处理得到EMST-CSS表示,该表示可以区分不同类别的视频。在具有无约束视频镜头的基准视频数据集上,使用精确召回度量对STAR的性能进行了定性和定量评估,以展示STAR的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
STAR: A Content Based Video Retrieval system for moving camera video shots
This paper presents the design of STAR (Spatio-Temporal Analysis and Retrieval), an unsupervised Content Based Video Retrieval (CBVR) System. STAR's key insight and primary contribution is that it models video content using a joint spatio-temporal feature representation and retrieves videos from the database which have similar moving object and trajectories of motion. Foreground moving blobs from a moving camera video shot are extracted, along with a trajectory for camera motion compensation, to form the space-time volume (STV). The STV is processed to obtain the EMST-CSS representation, which can discriminate across different categories of videos. Performance of STAR has been evaluated qualitatively and quantitatively using precision-recall metric on benchmark video datasets having unconstrained video shots, to exhibit efficiency of STAR.
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