Direct visual hazard affordance detection
McMahon, Sean M. (2019) Direct visual hazard affordance detection. PhD by Publication, Queensland University of Technology.
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Sean McMahon Thesis
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Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. |
Description
This research investigates how robotic and autonomous perceptual systems can detect the action possibilities, or affordances, of objects in their environment. Specifically, hazard affordances are detected, as they are a type of detrimental action allowed by some objects. Trip hazard detection on construction sites is the primary, but not the only application domain of this direct visual affordance detection approach.
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| ID Code: | 129572 |
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| Item Type: | QUT Thesis (PhD by Publication) |
| Supervisor: | Milford, Michael & Suenderhauf, Niko |
| Keywords: | Visual Affordance Detection, Affordance Detection, Affordances, Robotic Vision, Deep Learning, Computer Vision, Robotics |
| DOI: | 10.5204/thesis.eprints.129572 |
| Divisions: | Past > QUT Faculties & Divisions > Science & Engineering Faculty Past > Schools > School of Electrical Engineering & Computer Science |
| Institution: | Queensland University of Technology |
| Deposited On: | 18 Jun 2019 13:30 |
| Last Modified: | 17 Jan 2025 00:48 |
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