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DC Field | Value | Language |
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dc.contributor.author | Roopalakshmi, R. | - |
dc.contributor.author | Ram Mohana Reddy, Guddeti | - |
dc.date.accessioned | 2020-03-31T06:51:11Z | - |
dc.date.available | 2020-03-31T06:51:11Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Signal, Image and Video Processing, 2015, Vol.9, 1, pp.201-210 | en_US |
dc.identifier.uri | 10.1007/s11760-013-0424-7 | - |
dc.identifier.uri | https://idr.nitk.ac.in/jspui/handle/123456789/9598 | - |
dc.description.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. 2013, Springer-Verlag London. | en_US |
dc.title | A framework for estimating geometric distortions in video copies based on visual-audio fingerprints | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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