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dc.contributor.authorRoopalakshmi, R.-
dc.contributor.authorRam Mohana Reddy, Guddeti-
dc.date.accessioned2020-03-31T06:51:11Z-
dc.date.available2020-03-31T06:51:11Z-
dc.date.issued2015-
dc.identifier.citationSignal, Image and Video Processing, 2015, Vol.9, 1, pp.201-210en_US
dc.identifier.uri10.1007/s11760-013-0424-7-
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/9598-
dc.description.abstractSpatio-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. 2013, Springer-Verlag London.en_US
dc.titleA framework for estimating geometric distortions in video copies based on visual-audio fingerprintsen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

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