Open AccessAn Efficient and Robust Temporal Video Segmentation
Author(s) -
Jasmin T. Jose*,
S Rajkumar
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1812.109119
Subject(s) - automatic summarization , computer science , search engine indexing , artificial intelligence , segmentation , shot (pellet) , video tracking , feature (linguistics) , feature extraction , computer vision , focus (optics) , video retrieval , pattern recognition (psychology) , video processing , linguistics , chemistry , philosophy , physics , organic chemistry , optics
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 TRECVid, 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.