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Paper Abstract and Keywords
Presentation 2025-03-19 09:45
Neural Real-Time RGB-D SLAM in Dynamic Environments
Qinyuan Zhou, Kazuhiko Sumi (Aoyama Gakuin Univ.) PRMU2024-57
Abstract (in Japanese) (See Japanese page) 
(in English) Neural Simultaneous Localization and Mapping (SLAM) is a fundamental task in computer vision and robotics, enabling applications such as autonomous navigation and augmented reality. However, existing Neural SLAM methods are predominantly designed for static environments and often fail to account for dynamic elements, leading to reduced pose estimation accuracy. This paper presents a dynamic-aware neural RGB-D SLAM framework that incorporates geometric analysis and object detection to identify and mitigate the influence of dynamic regions in real-time. Temporal geometric changes are analyzed alongside deep learning-based object detection to refine map construction and improve pose estimation consistency. Furthermore, a point cloud filtering strategy is introduced to suppress the impact of dynamic objects on reconstruction. To evaluate neural SLAM performance under dynamic conditions, we propose a synthetic dataset augmentation method that integrates artificial dynamic elements into existing datasets. Experiments on the ScanNet dataset and our synthetic dataset demonstrate that the proposed approach improves Absolute Trajectory Error (ATE) RMSE compared to baseline models, leading to more stable mapping in dynamic environments.
Keyword (in Japanese) (See Japanese page) 
(in English) Neural SLAM / dynamic environments / RGB-D SLAM / object motion filtering / tracking estimation / synthetic dataset augmentation / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 445, PRMU2024-57, pp. 64-69, March 2025.
Paper # PRMU2024-57 
Date of Issue 2025-03-11 (PRMU) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2024-57

Conference Information
Committee PRMU IPSJ-CVIM IBISML  
Conference Date 2025-03-18 - 2025-03-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To PRMU 
Conference Code 2025-03-PRMU-CVIM-IBISML 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Neural Real-Time RGB-D SLAM in Dynamic Environments 
Sub Title (in English)  
Keyword(1) Neural SLAM  
Keyword(2) dynamic environments  
Keyword(3) RGB-D SLAM  
Keyword(4) object motion filtering  
Keyword(5) tracking estimation  
Keyword(6) synthetic dataset augmentation  
Keyword(7)  
Keyword(8)  
1st Author's Name Qinyuan Zhou  
1st Author's Affiliation Aoyama Gakuin University (Aoyama Gakuin Univ.)
2nd Author's Name Kazuhiko Sumi  
2nd Author's Affiliation Aoyama Gakuin University (Aoyama Gakuin Univ.)
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Speaker Author-1 
Date Time 2025-03-19 09:45:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2024-57 
Volume (vol) vol.124 
Number (no) no.445 
Page pp.64-69 
#Pages 6 
Date of Issue 2025-03-11 (PRMU) 

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