Author Type

Graduate Student

Date of Award

2014

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Kalva, Hari

Thesis/Dissertation Co-Chair

Raviv, Daniel

Abstract

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.

Extent

2:00 PM

Comments

Includes bibliography.|Thesis (M.S.)--Florida Atlantic University, 2014.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.

Identifier

FA00004104

Format

pdf

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Available for download on Thursday, October 06, 2196

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