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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2015(Vol.10, Issue:11)
Article Information:

A Framework for Automatic Video Surveillance Indexing and Retrieval

Fereshteh Falah Chamasemani, Lilly Suriani Affendey, Norwati Mustapha and Fatimah Khalid
Corresponding Author:  Fereshteh Falah Chamasemani 
Submitted: ‎February ‎13, ‎2015
Accepted: March ‎7, ‎2015
Published: August 15, 2015
Abstract:
The manual search through the surveillance video archives for a specific object or event is very time-consuming and tedious task due to the large volume of video data captured by many installed surveillance cameras. Therefore, the solution to accelerate and facilitate this process is to design an automatic video surveillance with the efficient and effective video indexing, video data model, query formulation and language, as well as visualization interface. There are many challenges, for developing a powerful query processing module, formulating complex queries and selecting suitable similarity matching strategy to detect any abnormality based on semantic content of the video using various query types. This study presents a novel video surveillance indexing and retrieval framework to cope with the above challenges. The proposed framework consists of three main modules i.e., pre-processing, query processing and retrieval processing. Moreover, it supports an efficient search and actively refines the retrieval result by formulating various query types including: query-by-text, query-by-example and query-by-region.

Key words:  Data modeling, query formulation, query processing, video indexing, video surveillance, video surveillance retrieval,
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Cite this Reference:
Fereshteh Falah Chamasemani, Lilly Suriani Affendey, Norwati Mustapha and Fatimah Khalid, . A Framework for Automatic Video Surveillance Indexing and Retrieval. Research Journal of Applied Sciences, Engineering and Technology, (11): 1316-1321.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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