An Efficient and Robust Temporal Video Segmentation
Jasmin T. Jose1, Rajkumar S.2
1Jasmin T. Jose*, Assistant Professor, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
2Rajkumar S, Associate Professor, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 4332-4337 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1812109119/2019©BEIESP | DOI: 10.35940/ijeat.A1812.109119
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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: Temporal video segmentation is the primary step of content based video retrieval. The whole processes of video management are coming under the focus of content based video retrieval, which includes, video indexing, video retrieval, and video summarization etc. In this paper, we proposed a computationally efficient and discriminating shot boundary detection method, which uses a local feature descriptor named local Contrast and Ordering (LCO) for feature extraction. The results of the experiments, which are conducted on the video dataset TRECV id, analyzed and compared with some existing shot boundary detection methods. The proposed method has given a promising result, even in the cases of illumination changes, rotated images etc.
Keywords: Shot Boundary Detection, Video retrieval, LCO, Abrupt Transition, Local descriptor.