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SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

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Comparative Analysis and Detection of Street Parked Vehicles using Spatiotemporal Maps and Corner Detection Methods

by Manali Jayebhaye, M.R.Banwaskar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 6
Year of Publication: 2016
Authors: Manali Jayebhaye, M.R.Banwaskar
10.5120/ijca2016908462

Manali Jayebhaye, M.R.Banwaskar . Comparative Analysis and Detection of Street Parked Vehicles using Spatiotemporal Maps and Corner Detection Methods. International Journal of Computer Applications. 136, 6 ( February 2016), 42-49. DOI=10.5120/ijca2016908462

@article{ 10.5120/ijca2016908462,
author = { Manali Jayebhaye, M.R.Banwaskar },
title = { Comparative Analysis and Detection of Street Parked Vehicles using Spatiotemporal Maps and Corner Detection Methods },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 6 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 42-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number6/24161-2016908462/ },
doi = { 10.5120/ijca2016908462 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:22.795322+05:30
%A Manali Jayebhaye
%A M.R.Banwaskar
%T Comparative Analysis and Detection of Street Parked Vehicles using Spatiotemporal Maps and Corner Detection Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 6
%P 42-49
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Traffic control and efficient use of existing infrastructure are key challenges in recent time. This work carries out comparative analysis of various corner detection methods in different conditions, to detect presence of parked vehicles in street lanes. Different algorithmic implementations are used, to detect corners over targets in video stream and then classify them over a spatio-temporal analysis maps to identify parked vehicles. The system has been evaluated using i-Lids public dataset and has proven to be robust against common difficulties found in Closed Circuit Television (CCTV) such as high noise levels, varying illumination and the presence of momentary occlusion by other vehicles. This could be used to detect illegal and double-parked vehicles in metropolitan areas and to detect incidents on roads with lanes. This paper implemented three corner detection algorithms, Harris, SIFT and FAST and analyzed the comparative performances of all three implementations over different parameters viz. precision, recall, false alarm and then conclude on best performing algorithm. The comparative results are presented.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Parked vehicle detection corner detection object classification spatiotemporal analysis and video analysis.

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