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Vehicle Tracking and Classification via 3D Geometries for Intelligent Transportation Systems
| Title: | Vehicle Tracking and Classification via 3D Geometries for Intelligent Transportation Systems. |
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| Name(s): |
Mcdowell, William, Author Mikhael, Wasfy, Committee Chair Jones, W Linwood, Committee Member Haralambous, Michael, Committee Member Atia, George, Committee Member Mahalanobis, Abhijit, Committee Member Muise, Robert, Committee Member University of Central Florida, Degree Grantor |
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| Type of Resource: | text | |
| Date Issued: | 2015 | |
| Publisher: | University of Central Florida | |
| Language(s): | English | |
| Abstract/Description: | In this dissertation, we present generalized techniques which allow for the tracking and classification of vehicles by tracking various Point(s) of Interest (PoI) on a vehicle. Tracking the various PoI allows for the composition of those points into 3D geometries which are unique to a given vehicle type. We demonstrate this technique using passive, simulated image based sensor measurements and three separate inertial track formulations. We demonstrate the capability to classify the 3D geometries in multiple transform domains (PCA (&) LDA) using Minimum Euclidean Distance, Maximum Likelihood and Artificial Neural Networks. Additionally, we demonstrate the ability to fuse separate classifiers from multiple domains via Bayesian Networks to achieve ensemble classification. | |
| Identifier: | CFE0005976 (IID), ucf:50790 (fedora) | |
| Note(s): |
2015-12-01 Ph.D. Engineering and Computer Science, Electrical Engineering and Computer Engineering Doctoral This record was generated from author submitted information. |
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| Subject(s): | Intelligent Transportation Systems -- Tracking -- Kalman Filters -- Classification | |
| Persistent Link to This Record: | http://purl.flvc.org/ucf/fd/CFE0005976 | |
| Restrictions on Access: | public 2015-12-15 | |
| Host Institution: | UCF |
