This thesis explores software algorithm for implementing a people counting and matching system to be used on a bus. A special camera is used, known as a texel camera, that generates depth and color information for a scene. This added information greatly facilitates both the tasks of matching and counting. Although people counting is a relatively mature field, there are several situations in which current technologies are not able to count correctly. Several of these difficult situations are tested with 82% counting accuracy. The idea of matching people on a bus is also developed. The goal is not to identify a specific person on a bus, but to find the time that a specific person is on the bus, and what bus stops were used. There are several aspects of this matching problem that differentiate it from other classification tasks that have been researched. In this thesis, multiple measurements are used to classify a person and sequence estimation techniques explored. The techniques developed classify with 92% accuracy, even with a relatively large number of people on a bus.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-1495 |
| Date | 01 December 2009 |
| Creators | Sallay, John |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact Andrew Wesolek (andrew.wesolek@usu.edu). |
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