Bio-inspired looming object detection using event-based cameras
dc.contributor.author | Sánchez Attolini, Guillermo | |
dc.contributor.author | University of Lethbridge. Faculty of Arts and Science | |
dc.contributor.supervisor | Cheng, Howard | |
dc.date.accessioned | 2020-02-20T23:39:28Z | |
dc.date.available | 2020-02-20T23:39:28Z | |
dc.date.issued | 2019 | |
dc.degree.level | Masters | en_US |
dc.description.abstract | We present a novel looming object detection method for event-based cameras. Event-based cameras capture a scene without generating redundant information thus reducing the needed transmission power, bandwidth, and computations to process the redundant information generated by conventional frame-based cameras. Regular computer vision algorithms cannot be directly applied to them. Conversely, existing event-based algorithms that detect looming objects have some limitations. In this thesis, an existing bio-inspired looming object detection algorithm for frame-based cameras was adapted for an event-based camera. The adapted algorithm was then used as part of a novel looming object detection algorithm that is fast and capable of detecting multiple looming objects in a scene. We tested our approach on the Davis Dynamic Vision Sensor event-based camera. | en_US |
dc.identifier.uri | https://hdl.handle.net/10133/5692 | |
dc.language.iso | en_US | en_US |
dc.proquest.subject | 0984 | en_US |
dc.proquestyes | Yes | en_US |
dc.publisher | Lethbridge, Alta. : Universtiy of Lethbridge, Department of Mathematics and Computer Science | en_US |
dc.publisher.department | Department of Mathematics and Computer Science | en_US |
dc.publisher.faculty | Arts and Science | en_US |
dc.relation.ispartofseries | Thesis (University of Lethbridge. Faculty of Arts and Science) | en_US |
dc.subject | Computer vision | en_US |
dc.subject | Computer algorithms | en_US |
dc.subject | Optics | en_US |
dc.subject | Digital images | en_US |
dc.subject | Deconvolution | en_US |
dc.subject | Dissertations, Academic | en_US |
dc.title | Bio-inspired looming object detection using event-based cameras | en_US |
dc.type | Thesis | en_US |