near-duplicate video retrieval current research and future trends pdf

Near-duplicate Video Retrieval Current Research And Future Trends Pdf

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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.

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Content based Video Retrieval using Text Annotation and Low Level Features Technique

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.

An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning. Buy Hardcover.

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. Specifically, we summarize and compare the definitions of near-duplicate videos NDVs in the literature, analyze the relationship between NDVR and its related research topics theoretically, describe its generic framework in detail, investigate the existing state-of-the-art NDVR systems.

Near-duplicate video retrieval: Current research and future trends

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.

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,

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.


Near-Duplicate Video Retrieval: Current Research and Future Trends. JIAJUN LIU, ZI HUANG, HONGYUN CAI, HENG TAO SHEN, The University of.


Multiscale video sequence matching for near-duplicate detection and retrieval

Единственная беда - Халохот глухой, с ним нельзя связаться по телефону. Недавно Стратмор сделал так, что Халохота снабдили новейшей игрушкой АНБ - компьютером Монокль. Себе Стратмор купил Скайпейджер, который запрограммировал на ту же частоту.

 - Я и понятия не имел.  - Его глаза сузились.  - Так к чему ты клонишь.

Near-duplicate video retrieval: Current research and future trends

Резко просигналив, пронесся мимо мини-автобус, до отказа забитый подростками. Мотоцикл Беккера показался рядом с ним детской игрушкой, выехавшей на автостраду. Метрах в пятистах сзади в снопе искр на шоссе выкатило такси. Набирая скорость, оно столкнуло в сторону Пежо-504, отбросив его на газон разделительной полосы.

Фонтейн сурово взглянул на. Уж о чем о чем, а о стрессовых ситуациях директор знал. Он был уверен, что чрезмерный нажим не приведет ни к чему хорошему.

Компьютерные вирусы столь же разнообразны, как и те, что поражают человека. Подобно своим природным аналогам они преследуют одну цель - внедриться в организм и начать размножаться. В данном случае организмом является ТРАНСТЕКСТ. Чатрукьяна всегда изумляло, что АНБ никогда прежде не сталкивалось с проблемой вирусов. Сквозь строй - надежная система, но ведь АНБ - ненасытный пожиратель информации, высасывающий ее из разнообразнейших источников по всему миру.

2 comments

Alexandra T.

Near-duplicate video retrieval: Current research and future trends. ACM Comput. Surv. 45, 4, Article 44 (August ), 23 pages. DOI: hc4hcommunityfair.org

REPLY

Nicolas B.

The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon.

REPLY

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