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Reseach Article

Multiple Video Instance Detection and Retrieval using Spatio-Temporal Analysis using Semi Supervised SVM Algorithm

by R. Kousalya, S. Dharani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 4
Year of Publication: 2017
Authors: R. Kousalya, S. Dharani
10.5120/ijca2017913495

R. Kousalya, S. Dharani . Multiple Video Instance Detection and Retrieval using Spatio-Temporal Analysis using Semi Supervised SVM Algorithm. International Journal of Computer Applications. 163, 4 ( Apr 2017), 12-19. DOI=10.5120/ijca2017913495

@article{ 10.5120/ijca2017913495,
author = { R. Kousalya, S. Dharani },
title = { Multiple Video Instance Detection and Retrieval using Spatio-Temporal Analysis using Semi Supervised SVM Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 4 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 12-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number4/27382-2017913495/ },
doi = { 10.5120/ijca2017913495 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:09:14.367468+05:30
%A R. Kousalya
%A S. Dharani
%T Multiple Video Instance Detection and Retrieval using Spatio-Temporal Analysis using Semi Supervised SVM Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 4
%P 12-19
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Object instance search aims to not solely retrieve the pictures or frames that contain the query, however additionally find all its occurrences. During this work, we tend to explore the utilization of spatio-temporal cues to enhance the standard of object instance search from videos. To the present finish, the work to formulate this drawback because the spatio-temporal trajectory search downside, wherever a trajectory may be a sequence of bounding boxes that find the thing instance in every frame. The goal is to seek out the top- trajectories that are possible to contain the target object. The work tends to solve the key bottleneck in applying the approach to object instance search by leverage a randomized approach to change quick marking of any bounding boxes within the video volume.

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Index Terms

Computer Science
Information Sciences

Keywords

Key-point localization SIFT descriptor Orientation Assignment Key-points descriptors Scale-space extrema detection.