Crowd estimation in images

Estimating the sizes of large crowds in images taken from high-mounted cameras is difficult, due to large variations of crowd density at different locations, as well as perspective distortion. This research project will investigate how the latest texture analysis methods and image processing techniq...

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Main Author: Sim, Long Terng.
Other Authors: Cham Tat Jen
Format: Final Year Project
Language:English
Published: 2012
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Online Access:http://hdl.handle.net/10356/48534
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-485342023-03-03T20:54:46Z Crowd estimation in images Sim, Long Terng. Cham Tat Jen School of Computer Engineering Centre for Multimedia and Network Technology DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Estimating the sizes of large crowds in images taken from high-mounted cameras is difficult, due to large variations of crowd density at different locations, as well as perspective distortion. This research project will investigate how the latest texture analysis methods and image processing techniques in computer vision can be used to help solve this problem. In this project, we will look through multiple techniques in estimating crowd size from a distance. The first experiment estimates the crowd size on "Jacob's Method", which uses basic geometric calculation to estimate a crowd density. Using this methodology, we are able to get an estimated result but the accuracy and correctness of the result is hard to be proven. To refine the estimation of crowd density, we investigate the use of color detection and edge detection technique that can be applied to calculate and estimate the crowd size in the images. The distance of the images has to be taken from approximately 20 to 50 meters away to get a clear view of the human skin color for higher detection rate. By applying Hue Saturation Value (HSV) color-space detection technique, the system is able to detect a range of skin-tone colors. Single successful skin color detection would be counted as a blob, depending on the number of blobs; the system is able to estimate the amount of people in the image. Digital images are captured in 2-dimensional array of numbers and each number represents a pixel. Matlab has vast methods in array manipulation and a wide range of image processing libraries which is the most optimal platform for coding out the system and hence, is use as the development tool for this research project Bachelor of Engineering (Computer Science) 2012-04-26T01:05:46Z 2012-04-26T01:05:46Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48534 en Nanyang Technological University 36 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Sim, Long Terng.
Crowd estimation in images
description Estimating the sizes of large crowds in images taken from high-mounted cameras is difficult, due to large variations of crowd density at different locations, as well as perspective distortion. This research project will investigate how the latest texture analysis methods and image processing techniques in computer vision can be used to help solve this problem. In this project, we will look through multiple techniques in estimating crowd size from a distance. The first experiment estimates the crowd size on "Jacob's Method", which uses basic geometric calculation to estimate a crowd density. Using this methodology, we are able to get an estimated result but the accuracy and correctness of the result is hard to be proven. To refine the estimation of crowd density, we investigate the use of color detection and edge detection technique that can be applied to calculate and estimate the crowd size in the images. The distance of the images has to be taken from approximately 20 to 50 meters away to get a clear view of the human skin color for higher detection rate. By applying Hue Saturation Value (HSV) color-space detection technique, the system is able to detect a range of skin-tone colors. Single successful skin color detection would be counted as a blob, depending on the number of blobs; the system is able to estimate the amount of people in the image. Digital images are captured in 2-dimensional array of numbers and each number represents a pixel. Matlab has vast methods in array manipulation and a wide range of image processing libraries which is the most optimal platform for coding out the system and hence, is use as the development tool for this research project
author2 Cham Tat Jen
author_facet Cham Tat Jen
Sim, Long Terng.
format Final Year Project
author Sim, Long Terng.
author_sort Sim, Long Terng.
title Crowd estimation in images
title_short Crowd estimation in images
title_full Crowd estimation in images
title_fullStr Crowd estimation in images
title_full_unstemmed Crowd estimation in images
title_sort crowd estimation in images
publishDate 2012
url http://hdl.handle.net/10356/48534
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