Filters








792 Hits in 3.2 sec

Self-Supervised 3D Keypoint Learning for Ego-motion Estimation [article]

Jiexiong Tang, Rares Ambrus, Vitor Guizilini, Sudeep Pillai, Hanme Kim, Patric Jensfelt, Adrien Gaidon
2020 arXiv   pre-print
In this work, we propose self-supervised learning of depth-aware keypoints directly from unlabeled videos.  ...  We describe how our self-supervised keypoints can be integrated into state-of-the-art visual odometry frameworks for robust and accurate ego-motion estimation of autonomous vehicles in real-world conditions  ...  by integrating our self-supervised, monocular and depth-aware keypoints into existing visual tracking frameworks such as Direct Sparse Odometry (DSO) [13] .  ... 
arXiv:1912.03426v3 fatcat:sxfvfyh75beivbiuzvb7prx2gq

Analysis of ROS-based Visual and Lidar Odometry for a Teleoperated Crawler-type Robot in Indoor Environment

Maxim Sokolov, Oleg Bulichev, Ilya Afanasyev
2017 Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics  
This article presents a comparative analysis of ROS-based monocular visual odometry, lidar odometry and ground truth-related path estimation for a crawler-type robot in indoor environment.  ...  The comparative analysis shown that lidar odometry is close to the ground truth, whereas visual odometry can demonstrate significant trajectory deviations. Sokolov, M., Bulichev, O. and Afanasyev, I.  ...  ROS-based LSD-SLAM Odometry Large-Scale Direct Monocular SLAM 8 (LSD-SLAM) creates a real-time global, semi-dense map in a fully direct mode without using keypoints, corners or any other local features  ... 
doi:10.5220/0006420603160321 dblp:conf/icinco/SokolovBA17 fatcat:7cix6m6ebfb2jhgkckcymr6cky

Extending Monocular Visual Odometry to Stereo Camera Systems by Scale Optimization [article]

Jiawei Mo, Junaed Sattar
2019 arXiv   pre-print
Additionally, direct scale optimization enables stereo visual odometry to be purely based on the direct method.  ...  The proposed method uses an additional camera to accurately estimate and optimize the scale of the monocular visual odometry, rather than triangulating 3D points from stereo matching.  ...  It combines the advantages of monocular visual odometry and stereo visual odometry, namely computational efficiency and scale awareness.  ... 
arXiv:1905.12723v3 fatcat:ieb7guvqfrev5j62lkopztaqzu

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.  ...  A monocular vision system and real-time scene understanding are computationally heavy and the major state-of-the-art algorithms are tested on high-end desktops and/or servers with a high CPU- and/or GPU  ...  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

Towards Scale Consistent Monocular Visual Odometry by Learning from the Virtual World [article]

Sen Zhang, Jing Zhang, Dacheng Tao
2022 arXiv   pre-print
Specifically, we first train a scale-aware disparity network using both monocular real images and stereo virtual data.  ...  Monocular visual odometry (VO) has attracted extensive research attention by providing real-time vehicle motion from cost-effective camera images.  ...  Scale-Aware Learning from Virtual Data Though it remains non-trivial to address the scale inconsistency problem solely from monocular training sequences, modern photorealisitic simulation engines open  ... 
arXiv:2203.05712v1 fatcat:rawwohdwwrbp7pspbnkoq4ikhq

Deep Direct Visual Odometry [article]

Chaoqiang Zhao, Yang Tang, Qiyu Sun, Athanasios V. Vasilakos
2021 arXiv   pre-print
Traditional monocular direct visual odometry (DVO) is one of the most famous methods to estimate the ego-motion of robots and map environments from images simultaneously.  ...  In addition, a new DVO architecture, called deep direct sparse odometry (DDSO), is proposed to overcome the drawbacks of the previous direct sparse odometry (DSO) framework by embedding TrajNet.  ...  In addition, we incorporate TrajNet with DSO [7] , called deep direct sparse odometry (DDSO).  ... 
arXiv:1912.05101v3 fatcat:ooa4y7aoxbhf3a2mpeanw7iwda

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction [article]

Huangying Zhan, Ravi Garg, Chamara Saroj Weerasekera, Kejie Li, Harsh Agarwal, Ian Reid
2018 arXiv   pre-print
At test time our framework is able to estimate single view depth and two-view odometry from a monocular sequence.  ...  sequences enables the use of both spatial (between left-right pairs) and temporal (forward backward) photometric warp error, and constrains the scene depth and camera motion to be in a common, real-world scale  ...  only direction is known.  ... 
arXiv:1803.03893v3 fatcat:uqdpu4ypafbq3fkieqfpowvhbi

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.  ...  The outstanding research results of deep learning visual odometry and deep learning loop closure detect are summarized.  ...  None declared. et al. then improved SVO by introducing Large-Scale Direct Monocular SLAM (LSD-SLAM) [25] which can run in largescale environments with CPU.  ... 
doi:10.1093/tse/tdz019 fatcat:c5tj64xro5ftvcw6qwz7rgrgky

D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry [article]

Nan Yang and Lukas von Stumberg and Rui Wang and Daniel Cremers
2020 arXiv   pre-print
We evaluate D3VO in terms of monocular visual odometry on both the KITTI odometry benchmark and the EuRoC MAV dataset.The results show that D3VO outperforms state-of-the-art traditional monocular VO methods  ...  We propose D3VO as a novel framework for monocular visual odometry that exploits deep networks on three levels -- deep depth, pose and uncertainty estimation.  ...  Instead of randomly initializing d p as in traditional monocular direct methods [16, 17] , we initialize the point with d p = D i [p] which provides the metric scale.  ... 
arXiv:2003.01060v2 fatcat:ph5rwawodfhdhhx62wnmyqxjee

Self-supervised Monocular Depth and Visual Odometry Learning with Scale-consistent Geometric Constraints

Mingkang Xiong, Zhenghong Zhang, Weilin Zhong, Jinsheng Ji, Jiyuan Liu, Huilin Xiong
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
The self-supervised learning-based depth and visual odometry (VO) estimators trained on monocular videos without ground truth have drawn significant attention recently.  ...  Specifically, we first align the scales of two reconstructed depth maps estimated from the adjacent image frames, and then enforce forward-backward relative pose consistency to formulate scale-consistent  ...  Without the utilization of traditional direct visual odometry, the proposed method outperforms DDVO .  ... 
doi:10.24963/ijcai.2020/134 dblp:conf/ijcai/XiongZZJLX20 fatcat:f34bauewyvgyrmaleppk63megy

Real Time Monocular Visual Odometry Using Hybrid Features and Distance Ratio for Scale Estimation

Diky Septa Nugroho, Igi Ardiyanto, Adha Imam Cahyadi
2018 International Journal on Advanced Science, Engineering and Information Technology  
The scale ambiguity for the monocular visual odometry becomes a challenging problem.  ...  Monocular visual odometry is a good choice as it is one of the dead reckoning navigation methods, which only uses a single camera.  ...  Algorithm Design In this work, we design a scale estimation algorithm for monocular visual odometry as shown in Fig. 5 .  ... 
doi:10.18517/ijaseit.8.5.3247 fatcat:57mefktrnbh6teqkkyrn64oipa

DeepVO: A Deep Learning approach for Monocular Visual Odometry [article]

Vikram Mohanty, Shubh Agrawal, Shaswat Datta, Arna Ghosh, Vishnu Dutt Sharma, Debashish Chakravarty
2016 arXiv   pre-print
This paper analyzes the problem of Monocular Visual Odometry using a Deep Learning-based framework, instead of the regular 'feature detection and tracking' pipeline approaches.  ...  propose a Convolutional Neural Network architecture, best suited for estimating the object's pose under known environment conditions, and displays promising results when it comes to inferring the actual scale  ...  Recently, fast direct monocular SLAM has also been achieved by the LSD-SLAM algorithm [7] .  ... 
arXiv:1611.06069v1 fatcat:b7gsha27cncg3gb3mt3yvdfode

Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos [article]

Jiaojiao Fang, Guizhong Liu
2021 arXiv   pre-print
In this paper, we explore the learnable occlusion aware optical flow guided self-supervised depth and camera pose estimation by an adaptive cross weighted loss to address the above limitations.  ...  Firstly, we explore to train the learnable occlusion mask fused optical flow network by an occlusion-aware photometric loss with the temporally supplemental information and backward-forward consistency  ...  Iterating this process at all scale levels can predict the multi-scales optical flow.  ... 
arXiv:2108.03893v3 fatcat:q2hvy5wcljbevh5vzy337jrcbe

Guided Feature Selection for Deep Visual Odometry [article]

Fei Xue, Qiuyuan Wang, Xin Wang, Wei Dong, Junqiu Wang, Hongbin Zha
2018 arXiv   pre-print
Different from current monocular visual odometry methods, our approach is established on the intuition that features contribute discriminately to different motion patterns.  ...  We present a novel end-to-end visual odometry architecture with guided feature selection based on deep convolutional recurrent neural networks.  ...  In § 2, related works on monocular VO and context-aware learning strategy are discussed. In § 3, we introduce the architecture of our Guided Feature Selection for Deep Visual Odometry.  ... 
arXiv:1811.09935v1 fatcat:dt2yhqilhfbkvgetg6egyarrki

Visual Odometry Revisited: What Should Be Learnt? [article]

Huangying Zhan, Chamara Saroj Weerasekera, Jiawang Bian, Ian Reid
2020 arXiv   pre-print
In this work we present a monocular visual odometry (VO) algorithm which leverages geometry-based methods and deep learning.  ...  Moreover, most monocular systems suffer from scale-drift issue.Some recent deep learning works learn VO in an end-to-end manner but the performance of these deep systems is still not comparable to geometry-based  ...  L ds is an edge-aware depth smoothness for regularization.  ... 
arXiv:1909.09803v4 fatcat:2yf6ozwtmbgj3bcete3ob4qgt4
« Previous Showing results 1 — 15 out of 792 results