A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
An efficient parts-based near-duplicate and sub-image retrieval system
Proceedings of the 12th annual ACM international conference on Multimedia
Towards effective indexing for very large video sequence database
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Communications of the ACM - Designing for the mobile device
Scaling and time warping in time series querying
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Detection of video sequences using compact signatures
ACM Transactions on Information Systems (TOIS)
A Time Warping Based Approach for Video Copy Detection
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Robust voting algorithm based on labels of behavior for video copy detection
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Practical elimination of near-duplicates from web video search
Proceedings of the 15th international conference 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
Bounded coordinate system indexing for real-time video clip search
ACM Transactions on Information Systems (TOIS)
Continuous Content-Based Copy Detection over Streaming Videos
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Online Near-Duplicate Video Clip Detection and Retrieval: An Accurate and Fast System
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Quality and efficiency in high dimensional nearest neighbor search
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Content-Based Copy Retrieval Using Distortion-Based Probabilistic Similarity Search
IEEE Transactions on Multimedia
An Image-Based Approach to Video Copy Detection With Spatio-Temporal Post-Filtering
IEEE Transactions on Multimedia
Spatiotemporal sequence matching for efficient video copy detection
IEEE Transactions on Circuits and Systems for Video Technology
Structure tensor series-based matching for near-duplicate video retrieval
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Real-time near-duplicate web video identification by tracking and matching of spatial features
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
ACM Transactions on Information Systems (TOIS)
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Since near duplicates are ubiquitous over different data sources, increasing research efforts have been put to near duplicate detection recently. Among all the near duplicate detection tasks, an important one is continuous near duplicate monitoring over video streams. Existing video monitoring techniques are not effective for handling the variations that commonly exist among near duplicates. Moreover, approaches proposed for the near duplicate detection in archived video databases are inefficient when applied to high speed video streams. In this work, we propose a framework for effectively online monitoring near duplicates over video streams. Specifically, we first propose a novel representation, a video cuboid signature, to describe a video segment. To capture the local spatio-temporal information of video subclips, we employ the Earth Mover's Distance (EMD) to measure the similarity between two signatures. Both the signature construction and the sequence similarity measure are incrementally processed by exploiting the inherent property of signature series. Then, we propose a novel scheme called locality sensitive multi-leveled approximation (LSMA) that optimizes the near duplicate video similarity matching over streams based on the locality sensitive hashing under EMD metric. The extensive experiments demonstrate the high performance of our approach in terms of the detection accuracy and time cost.