OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910576209297408 |
|---|---|
| author | Rahman, Muhammad Rameez ur Simonetto, Piero Polato, Anna Pasti, Francesco Tonin, Luca Vascon, Sebastiano |
| author_facet | Rahman, Muhammad Rameez ur Simonetto, Piero Polato, Anna Pasti, Francesco Tonin, Luca Vascon, Sebastiano |
| contents | Open vocabulary 3D object detection (OV3D) allows precise and extensible object recognition crucial for adapting to diverse environments encountered in assistive robotics. This paper presents OpenNav, a zero-shot 3D object detection pipeline based on RGB-D images for smart wheelchairs. Our pipeline integrates an open-vocabulary 2D object detector with a mask generator for semantic segmentation, followed by depth isolation and point cloud construction to create 3D bounding boxes. The smart wheelchair exploits these 3D bounding boxes to identify potential targets and navigate safely. We demonstrate OpenNav's performance through experiments on the Replica dataset and we report preliminary results with a real wheelchair. OpenNav improves state-of-the-art significantly on the Replica dataset at mAP25 (+9pts) and mAP50 (+5pts) with marginal improvement at mAP. The code is publicly available at this link: https://github.com/EasyWalk-PRIN/OpenNav. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_13936 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation Rahman, Muhammad Rameez ur Simonetto, Piero Polato, Anna Pasti, Francesco Tonin, Luca Vascon, Sebastiano Computer Vision and Pattern Recognition Open vocabulary 3D object detection (OV3D) allows precise and extensible object recognition crucial for adapting to diverse environments encountered in assistive robotics. This paper presents OpenNav, a zero-shot 3D object detection pipeline based on RGB-D images for smart wheelchairs. Our pipeline integrates an open-vocabulary 2D object detector with a mask generator for semantic segmentation, followed by depth isolation and point cloud construction to create 3D bounding boxes. The smart wheelchair exploits these 3D bounding boxes to identify potential targets and navigate safely. We demonstrate OpenNav's performance through experiments on the Replica dataset and we report preliminary results with a real wheelchair. OpenNav improves state-of-the-art significantly on the Replica dataset at mAP25 (+9pts) and mAP50 (+5pts) with marginal improvement at mAP. The code is publicly available at this link: https://github.com/EasyWalk-PRIN/OpenNav. |
| title | OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2408.13936 |