Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item A novel CBCD approach using MPEG-7 motion activity descriptors(2011) Roopalakshmi, R.; Guddeti, G.Motion features contribute significant information about a video content. This paper highlights a novel CBCD (Content-Based Copy Detection) approach, by incorporating several motion activity features. First, we extract both temporal and spatial motion features to describe overall activity of a video sequence. Second, we combine these features in a feasible manner, to generate robust video fingerprints. Third, clustering based pruned search is utilized for similarity matching instead of direct searching of video fingerprints. The proposed system is tested on TRECVID-2007 data set and the results demonstrate the effectiveness of the proposed system against several transformations such as random noise, fast forward, pattern insertion, cropping and picture-inside-picture. © 2011 IEEE.Item Towards a new approach to video copy detection using acoustic features(2011) Roopalakshmi, R.; Guddeti, G.Acoustic features are robust and powerful in video description, but not fully exploited for the emerging Content-Based video Copy Detection (CBCD) methods. To solve this discrepancy, this paper proposes a new CBCD approach using audio spectral features compared to existing visual content based methods. The proposed method incorporates three stages: 1) Extraction of spectral descriptors including centroid and energy; 2) Integration of resultant features to compute highly informative spectral descriptive words; 3) Utilization of clustering approach to speed up the similarity matching process. The results tested on TRECVID-2008 dataset, demonstrate the improved detection accuracy of proposed method (up to 27.845%) compared to reference methods against various transformations such as fast forward, slow motion, mp3 compression, and multiband companding. © 2011 IEEE.