EvMAPPER: High Altitude Orthomapping with Event Cameras
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929516310429696 |
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| author | Cladera, Fernando Chaney, Kenneth Hsieh, M. Ani Taylor, Camillo J. Kumar, Vijay |
| author_facet | Cladera, Fernando Chaney, Kenneth Hsieh, M. Ani Taylor, Camillo J. Kumar, Vijay |
| contents | Traditionally, unmanned aerial vehicles (UAVs) rely on CMOS-based cameras to collect images about the world below. One of the most successful applications of UAVs is to generate orthomosaics or orthomaps, in which a series of images are integrated together to develop a larger map. However, the use of CMOS-based cameras with global or rolling shutters mean that orthomaps are vulnerable to challenging light conditions, motion blur, and high-speed motion of independently moving objects under the camera. Event cameras are less sensitive to these issues, as their pixels are able to trigger asynchronously on brightness changes. This work introduces the first orthomosaic approach using event cameras. In contrast to existing methods relying only on CMOS cameras, our approach enables map generation even in challenging light conditions, including direct sunlight and after sunset. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_18120 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | EvMAPPER: High Altitude Orthomapping with Event Cameras Cladera, Fernando Chaney, Kenneth Hsieh, M. Ani Taylor, Camillo J. Kumar, Vijay Robotics Computer Vision and Pattern Recognition Traditionally, unmanned aerial vehicles (UAVs) rely on CMOS-based cameras to collect images about the world below. One of the most successful applications of UAVs is to generate orthomosaics or orthomaps, in which a series of images are integrated together to develop a larger map. However, the use of CMOS-based cameras with global or rolling shutters mean that orthomaps are vulnerable to challenging light conditions, motion blur, and high-speed motion of independently moving objects under the camera. Event cameras are less sensitive to these issues, as their pixels are able to trigger asynchronously on brightness changes. This work introduces the first orthomosaic approach using event cameras. In contrast to existing methods relying only on CMOS cameras, our approach enables map generation even in challenging light conditions, including direct sunlight and after sunset. |
| title | EvMAPPER: High Altitude Orthomapping with Event Cameras |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2409.18120 |