Paper Info
Title
Frame duplication detection based on BoW model.
Abstract
Duplicated sequence of frames in a video to cover up or replicate a scene is a video forgery. There are methods to authenticate video files, but embedding authentication information into videos requires extra hardware or software. It is possible to detect frame duplication forgery by carefully inspecting the content to discover high correlation among group of frames. A new frame duplication detection method based on Bag-of-Words (BoW) model is proposed in this paper. BoW is a model used in textual analysis first and image and video retrieval later by researchers. We used BoW to create visual words and build a dictionary from Scale Independent Feature Transform (SIFT) keypoints of frames in video. Frame features, i.e., visual word representations at keypoints, are used to detect sequence of duplicated parts in the video. The method computes thresholds depending on the content to improve both robustness and performance. The proposed method is tested on 31 test videos selected from Surrey University Library for Forensic Analysis (SULFA) and from various movies. Experimental results show a better detection performance and reduced run time compared to similar methods reported in the literature.
Year
DOI
Venue
2018
10.1007/s00530-017-0581-6
Multimedia Syst.
Field
DocType
Volume
Computer vision,Scale-invariant feature transform,Embedding,Authentication,Video retrieval,Computer science,Real-time computing,Robustness (computer science),Software,Artificial intelligence,Replicate,Visual Word
Journal
24
Issue
ISSN
Citations 
5
0942-4962
2
PageRank 
References 
Authors
0.36
23
4
Name
Order
Citations
PageRank
Güzin Ulutas16311.39
Ustubioglu, Beste2125.32
Mustafa Ulutas38311.05
Vasif V. Nabiyev412114.59