DynDex: a dynamic and non-metric space indexer
Proceedings of the tenth ACM international conference on Multimedia
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Automatic Selection and Combination of Descriptors for Effective 3D Similarity Search
ISMSE '04 Proceedings of the IEEE Sixth International Symposium on Multimedia Software Engineering
Dynamic similarity search in multi-metric spaces
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Video copy detection: a comparative study
Proceedings of the 6th ACM international conference on Image and video retrieval
Unified framework for fast exact and approximate search in dissimilarity spaces
ACM Transactions on Database Systems (TODS)
UQLIPS: a real-time near-duplicate video clip detection system
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient Similarity Search in Nonmetric Spaces with Local Constant Embedding
IEEE Transactions on Knowledge and Data Engineering
Content-Based Copy Retrieval Using Distortion-Based Probabilistic Similarity Search
IEEE Transactions on Multimedia
Spatiotemporal sequence matching for efficient video copy detection
IEEE Transactions on Circuits and Systems for Video Technology
Image retrieval and annotation using maximum entropy
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
| Hi-index | 0.00 |
Content-Based Video Copy Detection consists in retrieving all the modified versions of an original document in a video collection. It relies on two tasks: content description, for extracting one or many fingerprints from a video document, and similarity search, for determining the set of extracted fingerprints that make a close match. For the similarity search task, a copy detection system usually relies on a metric distance for measuring the degree of similarity between fingerprints. The metric properties represent a tradeoff between efficiency and effectiveness for a similarity search. A metric distance allows the use of well studied indexing structures. However, the metric properties restrict the similarity model that can be used for comparing two objects. For the present thesis, the main focus will be on researching similarity models for video sequences that do not necessarily comply the metric properties. In particular, we plan to research multi-metric and non-metric similarity measures for fulfilling effective and efficient detection. The issues involved in video copy detection (visual transformations, local and global fingerprints, temporal dimension, and approximated searches) make this problem a relevant topic for researching new similarity models.