Detection and classification for group moving humans

In the case of moving group of humans the recognition algorithms more often misclassify it as vehicles or large moving object. It is there fore the aim of this project to detect and classify moving object as either Group of humans or something else. The background subtraction technique has been empl...

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Main Author: Elgenaidi, Walid Suliman
Format: Thesis
Language:English
Published: 2007
Subjects:
Online Access:http://eprints.utm.my/5779/1/WalidSulimanElgenaidiMFKE2007.pdf
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author Elgenaidi, Walid Suliman
author_facet Elgenaidi, Walid Suliman
author_sort Elgenaidi, Walid Suliman
collection ePrints
description In the case of moving group of humans the recognition algorithms more often misclassify it as vehicles or large moving object. It is there fore the aim of this project to detect and classify moving object as either Group of humans or something else. The background subtraction technique has been employed in this work as it is able to provide complete feature of the moving object. However, it is extremely sensitive to dynamic changes like change of illumination. The detected foreground pixels usually contain noise, small movements like tree leaves. These isolated pixels are filtered by some of preprocessing operations; such as median filter and sequence of morphological operations dilation and erosion. Then the object will be extracted using border extraction technique. The classification makes use the shape of the object. The performance of the proposed technique has achieved 75% accuracy based on 18 test samples. This result shows that if it possible to distinctly classify a group of humans moving in the video sequence from other large moving objects such as vehicles.
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spelling utm.eprints-57792018-08-26T04:42:58Z http://eprints.utm.my/5779/ Detection and classification for group moving humans Elgenaidi, Walid Suliman TK Electrical engineering. Electronics Nuclear engineering TR Photography In the case of moving group of humans the recognition algorithms more often misclassify it as vehicles or large moving object. It is there fore the aim of this project to detect and classify moving object as either Group of humans or something else. The background subtraction technique has been employed in this work as it is able to provide complete feature of the moving object. However, it is extremely sensitive to dynamic changes like change of illumination. The detected foreground pixels usually contain noise, small movements like tree leaves. These isolated pixels are filtered by some of preprocessing operations; such as median filter and sequence of morphological operations dilation and erosion. Then the object will be extracted using border extraction technique. The classification makes use the shape of the object. The performance of the proposed technique has achieved 75% accuracy based on 18 test samples. This result shows that if it possible to distinctly classify a group of humans moving in the video sequence from other large moving objects such as vehicles. 2007-05 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/5779/1/WalidSulimanElgenaidiMFKE2007.pdf Elgenaidi, Walid Suliman (2007) Detection and classification for group moving humans. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:62131
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
TR Photography
Elgenaidi, Walid Suliman
Detection and classification for group moving humans
title Detection and classification for group moving humans
title_full Detection and classification for group moving humans
title_fullStr Detection and classification for group moving humans
title_full_unstemmed Detection and classification for group moving humans
title_short Detection and classification for group moving humans
title_sort detection and classification for group moving humans
topic TK Electrical engineering. Electronics Nuclear engineering
TR Photography
url http://eprints.utm.my/5779/1/WalidSulimanElgenaidiMFKE2007.pdf
work_keys_str_mv AT elgenaidiwalidsuliman detectionandclassificationforgroupmovinghumans