A Novel Retake Detection Using LCS and SIFT Algorithm

Authors:
Nagul Cooharojananone;Narongsak Putpuek;Shin'Ichi Satoh;Chidchanok Lursinsap
Affiliations:
Advanced Virtual and Intelligent Computing (AVIC) Center, Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand 10330;Advanced Virtual and Intelligent Computing (AVIC) Center, Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand 10330;National Institute of Informatics, Tokyo, Japan 101-8430;Advanced Virtual and Intelligent Computing (AVIC) Center, Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand 10330
Venue:
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2009

Citing 15
Cited 0

Information measure of location precision

Applied Mathematics and Computation
Object Recognition from Local Scale-Invariant Features

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
A Performance Evaluation of Local Descriptors

IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching slides to presentation videos using SIFT and scene background matching

MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Applying SIFT Descriptors to Stellar Image Matching

CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
A Comparison of Distance Measures for Clustering Video Sequences

DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
Video rushes summarization using spectral clustering and sequence alignment

TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
Video rushes summarization utilizing retake characteristics

TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
Rushes summarization using different redundancy elimination approaches

TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
Rushes summarization based on color, motion and face

TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
A distance measure for repeated takes of one scene

The Visual Computer: International Journal of Computer Graphics
Object re-detection using SIFT and MPEG-7 color descriptors

MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
Detecting and clustering multiple takes of one scene

MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Locating objects in a sensor grid

IWDC'04 Proceedings of the 6th international conference on Distributed Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a method to determine retake in rushes videos is proposed. This method first divides the video into shots, and then each shot that contains a single color, color bar or clapper board is eliminated. In each remaining shot, the similarity between consecutive frames is calculated using a SIFT matching algorithm and then converted into a string sequence. The similarity between two sequence is evaluated by the Longest Common Subsequence algorithm (LCS). This proposed SIFT - LCS based method was applied to the TRECVID BBC rushes videos of 2007 and 2008 as a competence test. The results support the notion that the proposed method provides a reasonably high degree of accuracy, and identifies the likely causes of poor accuracy for further improvements.