On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Finding Interesting Associations without Support Pruning
IEEE Transactions on Knowledge and Data Engineering
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Feature Extraction and a Database Strategy for Video Fingerprinting
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Robust content-based image searches for copyright protection
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Approximate searches: k-neighbors + precision
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical similarity search applied to content-based video copy detection
ICDEW '05 Proceedings of the 21st International Conference on Data Engineering Workshops
Scalability of local image descriptors: a comparative study
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Video copy detection: a comparative study
Proceedings of the 6th ACM international conference on Image and video retrieval
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Spatio–Temporal Transform Based Video Hashing
IEEE Transactions on Multimedia
Spatiotemporal sequence matching for efficient video copy detection
IEEE Transactions on Circuits and Systems for Video Technology
A Real-Time Content Based Video Copy Detection System
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Real-time keyframe extraction towards video content identification
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Scaling content-based video copy detection to very large databases
Multimedia Tools and Applications
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In the last few years, content-based video copy detection became an important and key tool for solving the tricky problem of video copyright protection. This problem has been heightened with the development of web video exchange platforms. In general, content-based video copy detection relies on the description of the visual content of the video. The video is segmented and a selected subset of frames, called keyframes, is described. Searching for a video is then performed by a set of similarity searches based on keyframes. These searches provide partial results that have to be integrated and fused. In this paper, we focus on this particular and crucial step. The objective is to properly fuse together partial results, to take into account the temporal coherence of the video and to be efficient (i.e. rapid). The solution we propose is based on a probabilistic framework that models the different parameters and inputs of this step and enables to deal with the temporal consistency. It also makes the process more reliable, as imprecision tolerated during the keyframe-based similarity searches has no impact on the overall accuracy. This particularly allows the speeding up of the detection process.