• AKETI SANTHOSH
• ANIL MOGURAM

If you have a large database, video resemblance checking is the most time-consuming and cost-effective task. Effective and fast manipulations of big video datasets are becoming increasingly desirable as the demand for visual information of rich content grows. Many studies on content-based video retrieval have been conducted. Despite its usefulness, video subsequence identification, which involves finding information that is comparable to a small query clip in a large video sequence, has received little attention. This work proposes a graph transformation and matching solution to this problem, with the goal of detecting the occurrence of potentially changed ordering or length as a result of content alteration. The mapping link between the query and database video is initially represented by a bipartite graph using a novel batch query approach to find related frames. The closely matched sections of the long sequence are then retrieved, and certain irrelevant subsequences are pruned using a filter-and-refine search approach. Maximum Size Matching is used during the filtering stage to reduce the number of candidates by constructing subgraphs from the query and candidate subsequence. Sub-Maximum Similarity Matching is used during the refinement step to find the subsequence with the highest aggregate score among all candidates, using a comprehensive video similarity model that takes into account visual content, temporal order, and frame alignment information.

PROCESSING VIDEO-BASED QUERIES IN A VIDEO STREAM

"PROCESSING VIDEO-BASED QUERIES IN A VIDEO STREAM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.193-198, February-2019, Available :http://www.jetir.org/papers/JETIRFE06035.pdf

"PROCESSING VIDEO-BASED QUERIES IN A VIDEO STREAM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp193-198, February-2019, Available at : http://www.jetir.org/papers/JETIRFE06035.pdf