6-DOF Pose Estimation For Event Cameras Using A Transformer-Based Approach
| dc.contributor.author | Tabia, Ahmed | |
| dc.contributor.author | Bonardi, Fabien | |
| dc.contributor.author | Bouchaa, Samia | |
| dc.contributor.editor | Skala, Václav | |
| dc.date.accessioned | 2025-07-30T09:31:08Z | |
| dc.date.available | 2025-07-30T09:31:08Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract-translated | Event cameras are novel sensors that provide significant advantages over traditional cameras, such as low latency, high dynamic range, and reduced motion blur. These properties make them particularly well-suited for 6-DOF pose estimation tasks in challenging environments. In this paper, we present a novel transformer-based approach for 6-DOF pose estimation using event camera data. Our method combines a pretrained ResNet50 backbone for feature extraction with a custom transformer encoder to model the spatial and temporal dependencies inherent in event data. We demonstrate the effectiveness of our approach on a dataset of real-world event camera images, where we achieve significant improvements in pose estimation accuracy compared to state-of-the-art methods. Additionally, our method exhibits robustness to varying lighting conditions, motion blur, and sensor noise, highlighting its potential for deployment in a wide range of applications, such as robotics, autonomous vehicles, and augmented reality. Our experimental results showcase the promising capabilities of transformer-based models in leveraging the unique properties of event cameras for accurate and efficient 6-DOF pose estimation. | en |
| dc.format | 8 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.identifier.doi | http://www.doi.org/10.24132/CSRN.2025-13 | |
| dc.identifier.issn | 2464-4617 (Print) | |
| dc.identifier.issn | 2464-4625 (online) | |
| dc.identifier.uri | http://hdl.handle.net/11025/62219 | |
| dc.language.iso | en | en |
| dc.publisher | Vaclav Skala - UNION Agency | en |
| dc.rights | © Vaclav Skala - UNION Agency | en |
| dc.rights.access | openAccess | en |
| dc.subject | odhad pózy v 6Dof | cs |
| dc.subject | hluboké učení | cs |
| dc.subject | transformace | cs |
| dc.subject | kamera založená na událostech | cs |
| dc.subject.translated | 6Dof pose estimation | en |
| dc.subject.translated | deep learning | en |
| dc.subject.translated | transforms | en |
| dc.subject.translated | event based camera | en |
| dc.title | 6-DOF Pose Estimation For Event Cameras Using A Transformer-Based Approach | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.type.status | Peer reviewed | en |
| dc.type.version | publishedVersion | en |
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