Model
Digital Document
Publisher
Florida Atlantic University
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.
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