Principal component neural networks: theory and applications
Principal component neural networks: theory and applications
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
Efficient Short Video Repeat Identification With Application to News Video Structure Analysis
IEEE Transactions on Multimedia
A Framework for Handling Spatiotemporal Variations in Video Copy Detection
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper we first propose a feature model clustering visual features for video copy recognition, and adopt Oriented PCA (OPCA) to compute subspace feature for robustness to video distortions and dimensionality reduction. We also propose a novel method to explore statistics of video database to estimate nearest neighbor classification error rate and learn the optimal classification threshold. Recognition performance is evaluated under significant video distortions and different video length. Results show that recognition error rate below 5% has been achieved under significant distortions, and subspace representation leads to much reduction of error rate compared to using original feature, especially for very short video clips (e.g.5s).