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Using Deep Learning Semantic Segmentation to Estimate Visual Odometry
| Title: | Using Deep Learning Semantic Segmentation to Estimate Visual Odometry. |
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| Name(s): |
Blankenship, Jason R., author Su, Hongbo, Thesis advisor Florida Atlantic University, Degree grantor College of Engineering and Computer Science Department of Civil, Environmental and Geomatics Engineering |
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| Type of Resource: | text | |
| Genre: | Electronic Thesis Or Dissertation | |
| Date Created: | 2018 | |
| Date Issued: | 2018 | |
| Publisher: | Florida Atlantic University | |
| Place of Publication: | Boca Raton, Fla. | |
| Physical Form: | application/pdf | |
| Extent: | 57 p. | |
| Language(s): | English | |
| Abstract/Description: | In this research, image segmentation and visual odometry estimations in real time are addressed, and two main contributions were made to this field. First, a new image segmentation and classification algorithm named DilatedU-NET is introduced. This deep learning based algorithm is able to process seven frames per-second and achieves over 84% accuracy using the Cityscapes dataset. Secondly, a new method to estimate visual odometry is introduced. Using the KITTI benchmark dataset as a baseline, the visual odometry error was more significant than could be accurately measured. However, the robust framerate speed made up for this, able to process 15 frames per second. | |
| Identifier: | FA00005990 (IID) | |
| Degree granted: | Thesis (M.S.)--Florida Atlantic University, 2018. | |
| Collection: | FAU Electronic Theses and Dissertations Collection | |
| Note(s): | Includes bibliography. | |
| Subject(s): |
Image segmentation Computer vision Deep learning Visual odometry |
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| Held by: | Florida Atlantic University Libraries | |
| Sublocation: | Digital Library | |
| Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00005990 | |
| Use and Reproduction: | Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. | |
| Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
| Host Institution: | FAU | |
| Is Part of Series: | Florida Atlantic University Digital Library Collections. |
