As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
In this paper, a two-level near-duplicate video detection method based on invariant moment was proposed. To reduce the computational complexity of near-duplicate video detection, a coarse-to-fine approach was adopted in the proposed method. The proposed method is composed of key-frame selection, invariant moment calculation, feature point extraction and matching, similarity measurement, and near-duplicate classifier. After key-frame selection, the proposed method coarsely finds the corresponding frame pairs based on invariant moments. For each chosen frame pair, SURF is used to find the corresponding point pairs between the query frame and the test one. After feature-level, spatial-level, and temporal-level similarity measurement, we can decide whether the query video clip and the test one are near-duplicate. The experimental results show that the proposed method can effectively detect near-duplicate videos. In addition, the proposed method has good performance against possible operations, re-scaling, and frame-rate change.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.