Note
Includes bibliography.
Member of
Contributors
Publisher
Florida Atlantic University
Date Issued
2014
EDTF Date Created
2014
Description
Many times we decide to go to a place depending on how crowded the place is.
Our decisions are made based on different aspects that are only known in real time. A
system that provides users or agencies information about the actual number of people in
the scene over the time will allow them to make a decision or have information about a
given location. This thesis presents a low complexity system for human counting and
human detection using public cameras which usually do not have good quality. The use
of computer vision techniques makes it possible to have a system that allows the user to
have an estimate number of people. Different videos were studied with different
resolutions and camera positions. The best video result shows an error of 0.269%, while
the worst one is 8.054 %. The results show that relatively inexpensive cameras streaming
video at a low bitrate can be used to develop large scale people counting applications.
Our decisions are made based on different aspects that are only known in real time. A
system that provides users or agencies information about the actual number of people in
the scene over the time will allow them to make a decision or have information about a
given location. This thesis presents a low complexity system for human counting and
human detection using public cameras which usually do not have good quality. The use
of computer vision techniques makes it possible to have a system that allows the user to
have an estimate number of people. Different videos were studied with different
resolutions and camera positions. The best video result shows an error of 0.269%, while
the worst one is 8.054 %. The results show that relatively inexpensive cameras streaming
video at a low bitrate can be used to develop large scale people counting applications.
Language
Type
Form
Extent
2 p.
Identifier
FA00004104
Additional Information
Includes bibliography.
Thesis (M.S.)--Florida Atlantic University, 2014.
FAU Electronic Theses and Dissertations Collection
Date Backup
2014
Date Created Backup
2014
Date Text
2014
Date Created (EDTF)
2014
Date Issued (EDTF)
2014
Extension
FAU
IID
FA00004104
Organizations
Attributed name: Florida Atlantic University
Attributed name: College of Engineering and Computer Science
Person Preferred Name
Escudero Huedo, Antonio Eliseo
author
Graduate College
Physical Description
application/pdf
2 p.
Title Plain
People counting and density estimation using public cameras
Use and Reproduction
Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
http://rightsstatements.org/vocab/InC/1.0/
Origin Information
2014
2014
Florida Atlantic University
Boca Raton, Fla.
Physical Location
Florida Atlantic University Libraries
Place
Boca Raton, Fla.
Sub Location
Digital Library
Title
People counting and density estimation using public cameras
Other Title Info
People counting and density estimation using public cameras