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Real-Time Monocular Object-Model Aware Sparse SLAM [article]

Mehdi Hosseinzadeh, Kejie Li, Yasir Latif, Ian Reid
2019 arXiv   pre-print
This work incorporates a real-time deep-learned object detector to the monocular SLAM framework for representing generic objects as quadrics that permit detections to be seamlessly integrated while allowing  ...  the real-time performance.  ...  CONCLUSIONS This work introduced a monocular SLAM system that can incorporate learned priors in terms of plane and object models in an online real-time capable system.  ... 
arXiv:1809.09149v2 fatcat:xgzexi7rkrfrxm2xi6zakjw5gu

DSP-SLAM: Object Oriented SLAM with Deep Shape Priors [article]

Jingwen Wang, Martin Rünz, Lourdes Agapito
2021 arXiv   pre-print
We propose DSP-SLAM, an object-oriented SLAM system that builds a rich and accurate joint map of dense 3D models for foreground objects, and sparse landmark points to represent the background.  ...  DSP-SLAM takes as input the 3D point cloud reconstructed by a feature-based SLAM system and equips it with the ability to enhance its sparse map with dense reconstructions of detected objects.  ...  Conclusions We have presented DSP-SLAM, a new object-aware real-time SLAM system that exploits deep shape priors for object reconstruction, produces a joint map of sparse Figure 7 : Object reconstruction  ... 
arXiv:2108.09481v2 fatcat:2cxcoerz6vfjnkju5oskhxxuie

SLAM-based dense surface reconstruction in monocular Minimally Invasive Surgery and its application to Augmented Reality

Long Chen, Wen Tang, Nigel W. John, Tao Ruan Wan, Jian Jun Zhang
2018 Computer Methods and Programs in Biomedicine  
Both camera tracking and surface reconstruction based on a sparse point cloud are effective and operated in real-time.  ...  A robust global 3D surface reconstruction framework has been developed for building a dense surface using only unorganized sparse point clouds extracted from the SLAM.  ...  These features can enable real-time endoscopic camera tracking and sparse point mapping in an abdominal cavity as shown in Figure 1 .  ... 
doi:10.1016/j.cmpb.2018.02.006 pmid:29544779 fatcat:v4bhbs7wzzej7pifadeffhwzqm

DSP-SLAM: Object Oriented SLAM with Deep Shape Priors

Jingwen Wang, Martin Runz, Lourdes Agapito
2021 2021 International Conference on 3D Vision (3DV)  
Figure 1: DSP-SLAM builds a rich object-aware map, providing complete detailed shapes of detected objects, while representing the background coarsely as sparse feature points.  ...  Conclusions We have presented DSP-SLAM, a new object-aware real-time SLAM system that exploits deep shape priors for object reconstruction, produces a joint map of sparse point features for the background  ...  [35] performed online exploration, learning object models on the fly and tracking them in real time.  ... 
doi:10.1109/3dv53792.2021.00143 fatcat:zle434gjcvaatklyfrt7dyhzze

A Survey of Simultaneous Localization and Mapping with an Envision in 6G Wireless Networks [article]

Baichuan Huang, Jun Zhao, Jingbin Liu
2020 arXiv   pre-print
The paper makes an overview in SLAM including Lidar SLAM, visual SLAM, and their fusion.  ...  It's very friendly for new researchers to hold the development of SLAM and learn it very obviously.  ...  Pixor: Real-time 3d object detection from point clouds.  ... 
arXiv:1909.05214v4 fatcat:itnluvkewfd6fel7x65wdgig3e

A Hybrid Sparse-Dense Monocular SLAM System for Autonomous Driving [article]

Louis Gallagher, Varun Ravi Kumar, Senthil Yogamani, John B. McDonald
2021 arXiv   pre-print
Global consistency and alignment between the sparse and dense models are achieved by applying pose constraints from the sparse method directly within the deformation of the dense model.  ...  In this paper, we present a system for incrementally reconstructing a dense 3D model of the geometry of an outdoor environment using a single monocular camera attached to a moving vehicle.  ...  models of indoor scenes in real-time with active depth sensors such as the Microsoft Kinect.  ... 
arXiv:2108.07736v1 fatcat:pk4vxikqd5fq5fwhdsa5ktqebe

CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations [article]

Hidenobu Matsuki, Raluca Scona, Jan Czarnowski, Andrew J. Davison
2021 arXiv   pre-print
We build on CodeSLAM and use a variational autoencoder (VAE) which is conditioned on intensity, sparse depth and reprojection error images from sparse SLAM to predict an uncertainty-aware dense depth map  ...  This flexible design allows for integration with arbitrary metric sparse SLAM systems without delaying the main SLAM process.  ...  Fig. 1 . 1 Top: Real-time dense mapping result (left: sparse SLAM, right: Fig. 3 Fig. 3 . 33 shows an overview of our system.  ... 
arXiv:2107.08994v1 fatcat:suf6x3hqnjgfdbj7awyj6nwr2y

Building an Integrated Mobile Robotic System for Real-Time Applications in Construction [article]

Khashayar Asadi, Hariharan Ramshankar, Harish Pullagurla, Aishwarya Bhandare, Suraj Shanbhag, Pooja Mehta, Spondon Kundu, Kevin Han, Edgar Lobaton, Tianfu Wu
2018 arXiv   pre-print
This is done by integrating contextual Awareness and visual SLAM into a ground robotics agent.  ...  in the environment in near real-time.  ...  When it comes to monocular vision-based SLAM, ORB-SLAM [19] , Direct Sparse Odometry (DSO) [20] and LSD-SLAM [21] are the widely used algorithms.  ... 
arXiv:1803.01745v3 fatcat:47jyqif53zcu3fkxdpmghded3m

DiT-SLAM: Real-Time Dense Visual-Inertial SLAM with Implicit Depth Representation and Tightly-Coupled Graph Optimization

Mingle Zhao, Dingfu Zhou, Xibin Song, Xiuwan Chen, Liangjun Zhang
2022 Sensors  
To well address these drawbacks, we propose DiT-SLAM, a novel real-time Dense visual-inertial SLAM with implicit depth representation and Tightly-coupled graph optimization.  ...  Recently, generating dense maps in real-time has become a hot research topic in the mobile robotics community, since dense maps can provide more informative and continuous features compared with sparse  ...  Although the light-weight sparse map is very suitable for real-time SLAM systems, it also limits its further applications, such as collision-free motion planning, surface-aware AR, or object recognition  ... 
doi:10.3390/s22093389 pmid:35591079 pmcid:PMC9102487 fatcat:cx6f55lcjbhlfiazhsykppmaiu

SLAM in the Field: An Evaluation of Monocular Mapping and Localization on Challenging Dynamic Agricultural Environment [article]

Fangwen Shu, Paul Lesur, Yaxu Xie, Alain Pagani, Didier Stricker
2020 arXiv   pre-print
This paper demonstrates a system capable of combining a sparse, indirect, monocular visual SLAM, with both offline and real-time Multi-View Stereo (MVS) reconstruction algorithms.  ...  Moreover, we highlight that our experiments provide meaningful insight to improve monocular SLAM systems under agricultural settings.  ...  To solve those practical issues, we decided to combine a sparse, feature-based monocular SLAM with both offline and real-time MVS reconstruction algorithm.  ... 
arXiv:2011.01122v2 fatcat:myxe7aoaszepxij37q6t522edq

Real-time Direct Monocular SLAM with Learning-based Confidence Estimation

Weiqi Zhang, Zifei Yan, Gang Xiao, Aidi Feng, Wangmeng Zuo
2019 IEEE Access  
To tackle the localization issue, we develop a novel real-time large-scale direct SLAM model, namely, GCP-SLAM, by integrating the learning-based confidence estimation into the depth fusion and motion  ...  Direct monocular simultaneous localization and mapping (SLAM) methods, for which the image intensity is used for tracking and mapping instead of sparse feature points, have gained in popularity in recent  ...  PTAM [6] is the first real-time monocular SLAM method which separated localization and mapping into two threads.  ... 
doi:10.1109/access.2019.2928578 fatcat:f6zkvtieyfh6xgwbiq3dcaijla

An Overview on Visual SLAM: From Tradition to Semantic

Weifeng Chen, Guangtao Shang, Aihong Ji, Chengjun Zhou, Xiyang Wang, Chonghui Xu, Zhenxiong Li, Kai Hu
2022 Remote Sensing  
Traditional visionbased SLAM research has made many achievements, but it may fail to achieve wished results in challenging environments.  ...  Deep learning has promoted the development of computer vision, and the combination of deep learning and SLAM has attracted more and more attention.  ...  Real-time monocular object SLAM is the most common one, using a large number of binary words and a database of object models to provide real-time detection.  ... 
doi:10.3390/rs14133010 fatcat:g45tav2qc5gchp46n6eunjvb2i

Simultaneous localisation and mapping of intelligent mobile robots

Sufang Wang, Tingyang Xie, Peng Chen
2021 International Journal of Cybernetics and Cyber-Physical Systems  
of monocular, binocular and RGB-D cameras in VSLAM, the ORB-SLAM2 system based on the feature extraction method, the LSD-SLAM system based on the direct method, and comprehensively understanding and comparing  ...  Simultaneous Localisation and Mapping (SLAM) is the key technology of mobile robot navigation. In this field, visual SLAM (VSLAM) has become a research hotspot in recent years.  ...  so it cannot have the real depth for all objects.  ... 
doi:10.1504/ijccps.2021.113103 fatcat:nuhj2zlfhjg4flrbykkfqzvwuy

Deep Learning for Visual SLAM in Transportation Robotics: A review

Chao Duan, Steffen Junginger, Jiahao Huang, Kairong Jin, Kerstin Thurow
2019 Transportation Safety and Environment  
Finally, future development directions of visual SLAM based on deep learning is prospected.  ...  In this paper, the latest research progress of deep learning applied to the field of visual SLAM is reviewed.  ...  [56] presented a unified method to recover from tracking failures and detect loop closures in the problem of monocular visual SLAM in real time.  ... 
doi:10.1093/tse/tdz019 fatcat:c5tj64xro5ftvcw6qwz7rgrgky

Fast 3D Semantic Mapping in Road Scenes

Xuanpeng Li, Dong Wang, Huanxuan Ao, Rachid Belaroussi, Dominique Gruyer
2019 Applied Sciences  
In this work, we propose a fast 3D semantic mapping system based on the monocular vision by fusion of localization, mapping, and scene parsing.  ...  In our framework, there is no need to make semantic inference on each frame of sequence, since the 3D point cloud data with semantic information is corresponding to sparse reference frames.  ...  Semi-Dense SLAM We explore LSD-SLAM to track camera's trajectory and build consistent, large-scale maps of the environment. LSD-SLAM is a real-time, semi-dense 3D mapping method.  ... 
doi:10.3390/app9040631 fatcat:3iqebmhknnbfphezkanwbbuex4
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