Date of Award:

12-2009

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Electrical and Computer Engineering

Committee Chair(s)

Scott Budge

Committee

Scott Budge

Committee

Jacob Gunther

Committee

Donald Cripps

Abstract

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.

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