Analysis and Detection of Content based Video Retrieval
Author(s) -
Shivanand S. Gornale,
Ashvini K Babaleshwar,
K Babaleshwar
Publication year - 2019
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2019.03.06
Subject(s) - computer science , video retrieval , domain (mathematical analysis) , region of interest , information retrieval , image retrieval , detector , artificial intelligence , multimedia , computer vision , image (mathematics) , telecommunications , mathematical analysis , mathematics
Content Based Video Retrieval (CBVR) System has been investigated over past decade it’s rooted in many applications like developments and technologies. The demand for extraction of high level semantics contents as well as handling of low level contents in video retrieval systems are still in need. Hence it motivates and encourages many researchers to discover their knowledge across CBVR domain and contribute their work to make the system more effective and useful in developing the system application. This paper highlights comprehensive and extensive review of CBVR techniques for detection of region of interest in a given video. The experiment is carried out for the detection of ROI using ACF detector. The detection rate of ROI is observed competitive and satisfactory.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom