File Name: near-duplicate video retrieval current research and future trends .zip
Emerging Internet services and applications attract increasing users to involve in diverse video-related activities, such as video searching, video downloading, video sharing and so on. As normal operations, they lead to an explosive growth of online video volume, and inevitably give rise to the massive near-duplicate contents. Near-duplicate video retrieval NDVR has always been a hot topic. The primary purpose of this paper is to present a comprehensive survey and an updated reviewof the advance on large-scaleNDVR to supply guidance for researchers.
Aniket Sugandhi and Deepshikha Sharma. International Journal of Computer Applications 14 , July The information retrieval processes are playing essential role in the computer based database exploration or finding the essential contents from the databases. Now in these days a number of search techniques and retrieval models are exist by using which the users can find the data. According to the different data formats the information retrieval processes are also varying therefore different data format based retrieval process are works in different manner. In this presented work the content based video retrieval model is presented. In the content based video retrieval model the work is initiated from the segmentation of the videos into the set of frames.
The exponential growth of online videos, along with the increasing user involvements to video-related activities, has been observed as a constant phenomenon during last decade. User's time spent on video capturing, editing, uploading, searching and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to the existence of a already-large amount of near-duplicate content. This imposes urgent demands on near-duplicate video retrieval as a key role in novel tasks such as video search, video copyright protection, video recommendation, and many more. Driven by its significance, near-duplicate video retrieval has recently attracted lots of attention.
As one of key technologies in content-based near-duplicate detection and video retrieval, video sequence matching can be used to judge whether two videos exist duplicate or near-duplicate segments or not. Despite a lot of research efforts devoted in recent years, how to precisely and efficiently perform sequence matching among videos which may be subject to complex audio-visual transformations from a large-scale database still remains a pretty challenging task. To address this problem, this paper proposes a multiscale video sequence matching MS-VSM method, which can gradually detect and locate the similar segments between videos from coarse to fine scales. At the coarse scale, it makes use of the Maximum Weight Matching MWM algorithm to rapidly select several candidate reference videos from the database for a given query. Then for each candidate video, its most similar segment with respect to the given query is obtained at the middle scale by the Constrained Longest Ascending Matching Subsequence CLAMS algorithm, and then can be used to judge whether that candidate exists near-duplicate or not.
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Each flow vector is binned according to itssprimary angle from the horizontal axis and weightedsaccording to its magnitude. To accelerate the framessimilarity computation, keyframes containing similar visualsfeatures are clustered by K-means clustering, and eachscluster is assigned a unique symbol. Keyframes within asclu Videos have To find a copy ofsa query video in a video Computer Science and Information Technologies, Vol.
Near-Duplicate Video Retrieval: Current Research and Future Trends. JIAJUN LIU, ZI HUANG, HONGYUN CAI, HENG TAO SHEN, The University of.
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Shen and C. The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon during the last decade.
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Near-duplicate video retrieval: Current research and future trends. ACM Comput. Surv. 45, 4, Article 44 (August ), 23 pages. DOI: hondapeople.orgReply
As one of key technologies in content-based near-duplicate detection and video retrieval, video sequence matching can be used to judge whether two videos exist duplicate or near-duplicate segments or not.Reply
The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon.Reply