Spatio-Temporal Alignment of Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Duplicate detection in consumer photography and news video
Proceedings of the tenth ACM international conference on Multimedia
Video retrieval using spatio-temporal descriptors
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Fast video matching with signature alignment
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Fast and robust short video clip search using an index structure
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Space-Time Behavior Based Correlation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Tracking news stories across different sources
Proceedings of the 13th annual ACM international conference on Multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Scalability of local image descriptors: a comparative study
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Robust voting algorithm based on labels of behavior for video copy detection
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Measuring novelty and redundancy with multiple modalities in cross-lingual broadcast news
Computer Vision and Image Understanding
A news video browser using identical video segment detection
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Content-Based Copy Retrieval Using Distortion-Based Probabilistic Similarity Search
IEEE Transactions on Multimedia
Scene duplicate detection based on the pattern of discontinuities in feature point trajectories
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Scalable mining of large video databases using copy detection
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Fast Content-Based Mining of Web2.0 Videos
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Places clustering of full-length film key-framesusing latent aspect modeling over SIFT matches
IEEE Transactions on Circuits and Systems for Video Technology
Evaluating detection of near duplicate video segments
Proceedings of the ACM International Conference on Image and Video Retrieval
Correlation-based retrieval for heavily changed near-duplicate videos
ACM Transactions on Information Systems (TOIS)
Near-duplicate video retrieval: Current research and future trends
ACM Computing Surveys (CSUR)
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Recently near duplicate shot detection attracts researchers attention. There are several promising applications of near duplicate detection, especially when applied to broadcast video streams. However, currently studied near duplicates are limited to: a) The same video material (footage) used several times in different programs (strict near duplicate), and b) Less strict near duplicates such as footages of the same objects or the same background (object duplicate). In this paper, we propose a method to detect scene duplicates, another type of near duplicate. This type of near duplicate is composed of different footages taking the same scene, the same event, at the same time, but from the different viewpoints, e.g., by the different cameras, and possibly with temporal offsets. This type of near duplicate is particularly useful to identify the same event reported in the different programs and especially by the different broadcast stations. To handle this, we employ matching of temporal pattern of discontinuities obtained from trajectories of feature points. To detect discontinuities and to match trajectories, we used inconsistency. The method is accelerated by two-stage approach: the first stage is filtering by using temporal discontinuity patterns, and the second is precise matching by normalized cross correlation between inconsistency sequences of trajectories. The first stage is further accelerated by using interval histograms. Its performance is demonstrated with actual broadcasted videos from five channels and three hours from each channel, in total 15 hours.