Human tracking with active camera (U-TrAC)

Tracking of deformable objects is an active area of research in the field of machine vision. It is useful for many vision-based systems such as video surveillance systems. Some difficulties encountered in some of the researchers are the automatic identification of blobs as humans through body shape...

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Main Authors: Arcilla, Jon Ronald N., Co, Edniel A., Matibag, Michael T., Regis, Caya Ishbel C.
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Language:English
Published: Animo Repository 2006
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/14183
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-148252021-11-10T14:48:10Z Human tracking with active camera (U-TrAC) Arcilla, Jon Ronald N. Co, Edniel A. Matibag, Michael T. Regis, Caya Ishbel C. Tracking of deformable objects is an active area of research in the field of machine vision. It is useful for many vision-based systems such as video surveillance systems. Some difficulties encountered in some of the researchers are the automatic identification of blobs as humans through body shape and motion, avoidance of false alarms due to lighting and background changes, and the robustness of the system to occlusions. Human tracking with Active Camera (U-TrAC) is a system that detects and tracks human from a given input video stream, taken using an active camera platform. The web camera is placed on an electro-mechanical platform that is positioned at the center of the ceiling of the room to be observed. The system is capable of rotating the camera 360 horizontally and tilting it 90 vertically at a rate of 7 revolutions per minute (rpm) or 40 per second. By panning and tilting the camera around, the system looks for a human body, using a cascaded classifier that is trained with 176 positive and 610 negative samples and consisting of 16 stages for human body detection. The human body moving at a maximum rate of 4.0 km/hr may be detected from 3.3 meters to as much as 16.6 meters away from the camera. The human body could be detected as long as it is standing upright, presenting a front or back view and the contrast ratio of the human body to the background is at most 26:66. The tracking technique is robust to partial occlusions. The system is able to maintain the tracking of the human body in spite of partial occlusions provided the occlusion will not obstruct the centroid or the tracking point of the human body. 2006-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/14183 Bachelor's Theses English Animo Repository Image processing--Digital techniques Computer vision Cameras Photography Computer Sciences
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Image processing--Digital techniques
Computer vision
Cameras
Photography
Computer Sciences
spellingShingle Image processing--Digital techniques
Computer vision
Cameras
Photography
Computer Sciences
Arcilla, Jon Ronald N.
Co, Edniel A.
Matibag, Michael T.
Regis, Caya Ishbel C.
Human tracking with active camera (U-TrAC)
description Tracking of deformable objects is an active area of research in the field of machine vision. It is useful for many vision-based systems such as video surveillance systems. Some difficulties encountered in some of the researchers are the automatic identification of blobs as humans through body shape and motion, avoidance of false alarms due to lighting and background changes, and the robustness of the system to occlusions. Human tracking with Active Camera (U-TrAC) is a system that detects and tracks human from a given input video stream, taken using an active camera platform. The web camera is placed on an electro-mechanical platform that is positioned at the center of the ceiling of the room to be observed. The system is capable of rotating the camera 360 horizontally and tilting it 90 vertically at a rate of 7 revolutions per minute (rpm) or 40 per second. By panning and tilting the camera around, the system looks for a human body, using a cascaded classifier that is trained with 176 positive and 610 negative samples and consisting of 16 stages for human body detection. The human body moving at a maximum rate of 4.0 km/hr may be detected from 3.3 meters to as much as 16.6 meters away from the camera. The human body could be detected as long as it is standing upright, presenting a front or back view and the contrast ratio of the human body to the background is at most 26:66. The tracking technique is robust to partial occlusions. The system is able to maintain the tracking of the human body in spite of partial occlusions provided the occlusion will not obstruct the centroid or the tracking point of the human body.
format text
author Arcilla, Jon Ronald N.
Co, Edniel A.
Matibag, Michael T.
Regis, Caya Ishbel C.
author_facet Arcilla, Jon Ronald N.
Co, Edniel A.
Matibag, Michael T.
Regis, Caya Ishbel C.
author_sort Arcilla, Jon Ronald N.
title Human tracking with active camera (U-TrAC)
title_short Human tracking with active camera (U-TrAC)
title_full Human tracking with active camera (U-TrAC)
title_fullStr Human tracking with active camera (U-TrAC)
title_full_unstemmed Human tracking with active camera (U-TrAC)
title_sort human tracking with active camera (u-trac)
publisher Animo Repository
publishDate 2006
url https://animorepository.dlsu.edu.ph/etd_bachelors/14183
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