Abstract
Spatio-temporal alignments and estimation of distortion model between pirate and master video contents are prerequisites, in order to approximate the illegal capture location in a theater. State-of-the-art techniques are exploiting only visual features of videos for the alignment and distortion model estimation of watermarked sequences, while few efforts are made toward acoustic features and non-watermarked video contents. To solve this, we propose a distortion model estimation framework based on multimodal signatures, which fully integrates several components: Compact representation of a video using visual-audio fingerprints derived from Speeded Up Robust Features and Mel-Frequency Cepstral Coefficients; Segmentation-based bipartite matching scheme to obtain accurate temporal alignments; Stable frame pairs extraction followed by filtering policies to achieve geometric alignments; and distortion model estimation in terms of homographic matrix. Experiments on camcorded datasets demonstrate the promising results of the proposed framework compared to the reference methods.
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This research work is supported by Department of Science & Technology (DST) of Government of India under research grant no. SR/WOS-A/ET-48/2010.
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Roopalakshmi, R., Reddy, G.R.M. A framework for estimating geometric distortions in video copies based on visual-audio fingerprints. SIViP 9, 201–210 (2015). https://doi.org/10.1007/s11760-013-0424-7
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DOI: https://doi.org/10.1007/s11760-013-0424-7