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Comparison of Optical Flow Algorithms for Speed Determination of Moving Objects

by Ekta Patel, Dolley Shukla
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 63 - Number 5
Year of Publication: 2013
Authors: Ekta Patel, Dolley Shukla
10.5120/10465-5180

Ekta Patel, Dolley Shukla . Comparison of Optical Flow Algorithms for Speed Determination of Moving Objects. International Journal of Computer Applications. 63, 5 ( February 2013), 32-37. DOI=10.5120/10465-5180

@article{ 10.5120/10465-5180,
author = { Ekta Patel, Dolley Shukla },
title = { Comparison of Optical Flow Algorithms for Speed Determination of Moving Objects },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 63 },
number = { 5 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume63/number5/10465-5180/ },
doi = { 10.5120/10465-5180 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:13:23.294831+05:30
%A Ekta Patel
%A Dolley Shukla
%T Comparison of Optical Flow Algorithms for Speed Determination of Moving Objects
%J International Journal of Computer Applications
%@ 0975-8887
%V 63
%N 5
%P 32-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we present a semi real-time vehicle tracking algorithm to determine the speed of the vehicles in traffic from traffic cam video. The results of this work can be used for traffic control, security and safety both by government agencies and commercial organizations. In this paper a method is described for tracking moving objects from a sequence of video frame. This method is implemented by using optical flow (Horn-Schunck)and (Lucas-Kanade) in mat lab and Simulink. It has a variety of uses, some of which are: human computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging and video editing. Segmentation is performed to detect the object after reducing the noise from that scene. The object is tracked by plotting a rectangular bounding box around it in each frame. The velocity of the object is determined by calculating the distance that the object moved in a sequence of frames with respect to the frame rate that the video is recorded. Comparison and performance analysis of algorithms based on psnr and average angular error is done.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Tracking Optical flow Motion estimation Lucas-Kanade algorithm

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