near-duplicate video retrieval current research and future trends pdf

Near-duplicate Video Retrieval Current Research And Future Trends Pdf

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Published: 19.03.2021

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.

An application within AI that has gained attention is machine learning.

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.

Multiscale video sequence matching for near-duplicate detection and retrieval

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. As such, the MS-VSM method can achieve excellent near-duplicate detection accuracy and localization precision with a very high processing efficiency. Extensive experiments show that it outperforms several state-of-the-art methods remarkably on several benchmarks.

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 discovered in recent works, latest improvements and progresses in near-duplicate video retrieval as well as related topics including low-level feature extraction, signature generation and high-dimensional indexing, are employed to assist the process.

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. User's time spent on video capturing, editing, uploading, searching, and viewing has boosted to an unprecedented level.

Multiscale video sequence matching for near-duplicate detection and retrieval

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. As such, the MS-VSM method can achieve excellent near-duplicate detection accuracy and localization precision with a very high processing efficiency.

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. Given asreference database and a query video,

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Near-duplicate video retrieval: Current research and future trends

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Он все рассказал, нажал клавишу PRINT и застрелился. Хейл поклялся, что никогда больше не переступит порога тюрьмы, и сдержал слово, предпочтя смерть. - Дэвид… - всхлипывала.  - Дэвид.

 Hola? - крикнул он, приоткрыв дверь.  - Con permiso. Не дождавшись ответа, он вошел. Типичная для Испании туалетная комната: квадратная форма, белый кафель, с потолка свисает единственная лампочка. Как всегда, одна кабинка и один писсуар.

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Вторая попытка также ни к чему не привела. Беккер заглянул в телефонный справочник. Оставался последний номер. Конец веревочки. Он набрал номер.

Near-duplicate video retrieval: Current research and future trends

 Идемте, мисс Флетчер, - сказал Фонтейн и прошел.  - Нам сейчас пригодится любая помощь. Посверкивая в красноватом свете туннельных ламп, перед ними возникла стальная дверь. Фонтейн набрал код на специальной углубленной панели, после чего прикоснулся к небольшой стеклянной пластинке.

Если я и полицейский, то уж точно не здешний, как ты думаешь. Эти слова, похоже, озадачили панка. - Меня зовут Дэвид Беккер.  - Беккер улыбнулся и над столом протянул парню руку.

Я был ослеплен своими амбициями. Стоя над Хейлом и стараясь унять дрожь, Сьюзан услышала приближающиеся шаги и медленно обернулась. В проломе стены возникла фигура Стратмора. Он был бледен и еле дышал.

Он быстро нацарапал на программке ответ и протянул Сьюзан: LDSNN Сьюзан, прочитав, просияла.

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