A Scheme for Shot Detection and Video Retreival using Spatio Temporal Features
G S Naveen Kumar1, V S K Reddy2
1G S Naveen Kumar, Research Scholar, Faculty of Engineering, Lincoln University College, Malaysia.
2V S K Reddy, Professor, Faculty of Engineering, Lincoln University College, Malaysia.
Manuscript received on 20 September 2019 | Revised Manuscript received on 06 October 2019 | Manuscript Published on 11 October 2019 | PP: 605-608 | Volume-8 Issue-2S10 September 2019 | Retrieval Number: B11390982S1019/2019©BEIESP | DOI: 10.35940/ijrte.B1139.0982S1019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There has been a revolution in multimedia with technological advancement. Hence, Video recording has increased in leaps and bounds. Video retrieval from a huge database is cumbersome by the existing text based search since a lot of human effort is involved and the retrieval efficiency is meager as well. In view of the present challenges, video retrieval based on video content prevails over the existing conventional methods. Content implies real video information such as video features. The performance of the Content Based Video Retrieval (CBVR) depends on Feature extraction and similar features matching. Since the selection of features in the existing algorithms is not effective, the retrieval processing time is more and the efficiency is less. Combined features of color and motion have been proposed for feature extraction and Spatio-Temporal Scale Invariant Feature Transform is used for Shot Boundary Detection. Since the characteristic of color feature is visual video content and that of motion feature is temporal content, these two features are significant in effective video retrieval. The performance of the CBVR system has been evaluated on the TRECVID dataset and the retrieved videos reveal the effectiveness of proposed algorithm.
Keywords: Shot Transition, Selective Frames, Integrated Feature Extraction, Feature Matching, Retrieval.
Scope of the Article: Nanometer-Scale Integrated Circuits