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In this paper, we propose two video fingerprinting methods that are robust to both geometric and non-geometric modifications on content. Both of the proposed methods are based on computation of moment invariants as features from concentric circular regions. The two methods differ in the way they capture appearance and motion information from video. In one method, we capture motion information by computing...
In this paper, we study the collision property of one of the robust hash functions proposed. This method was originally proposed for robust hash generation from blocks of image data and is based on projection of image block data on pseudo-random matrices. We show that collision performance of this robust hash function is not optimal when used to extract hash bits from a moment invariants feature matrix...
We present a novel video fingerprinting method based on subspace embedding. The proposed method is particularly robust against frame-rate conversion attacks and geometric attacks among other attacks including compression and spatial scaling. Using a sliding window, we extract fingerprints from a group of subsequent video frames. For the generation of the fingerprints, we first calculate the basis...
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