Object-Based Change Detection Algorithm with a Spatial AI Stereo Camera
Göncz, L and Majdik, András (2022) Object-Based Change Detection Algorithm with a Spatial AI Stereo Camera. SENSORS, 22 (17). ISSN 1424-8220 10.3390/s22176342
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Abstract
This paper presents a real-time object-based 3D change detection method that is built around the concept of semantic object maps. The algorithm is able to maintain an object-oriented metric-semantic map of the environment and can detect object-level changes between consecutive patrol routes. The proposed 3D change detection method exploits the capabilities of the novel ZED 2 stereo camera, which integrates stereo vision and artificial intelligence (AI) to enable the development of spatial AI applications. To design the change detection algorithm and set its parameters, an extensive evaluation of the ZED 2 camera was carried out with respect to depth accuracy and consistency, visual tracking and relocalization accuracy and object detection performance. The outcomes of these findings are reported in the paper. Moreover, the utility of the proposed object-based 3D change detection is shown in real-world indoor and outdoor experiments.
| Item Type: | Article |
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| Subjects: | Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány |
| Divisions: | Distributed Events Analysis Research Laboratory |
| SWORD Depositor: | MTMT Injector |
| Depositing User: | MTMT Injector |
| Date Deposited: | 22 Sep 2022 07:49 |
| Last Modified: | 11 Sep 2023 15:07 |
| URI: | https://eprints.sztaki.hu/id/eprint/10377 |
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