Results 21 to 30 of about 2,698 (178)
Advances in Neural Information Processing Systems 36, 2023 We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for monocular Visual Odometry (VO). DPVO uses a novel recurrent network architecture designed for tracking image patches across time. Recent approaches to VO have significantly improved the state-of-the-art accuracy by using deep networks to predict dense flow between video frames.
Zachary Teed +2 more
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A Novel Visual SLAM Based on Multiple Deep Neural Networks
Applied Sciences, 2023 The current visual simultaneous localization and mapping (SLAM) systems require the use of matched feature point pairs to estimate camera pose and construct environmental maps.
Bihong Zhu +4 more
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Pseudo-LiDAR for Visual Odometry
IEEE Transactions on Instrumentation and Measurement, 2023 In the existing methods, LiDAR odometry shows superior performance, but visual odometry is still widely used for its price advantage. Conventionally, the task of visual odometry mainly rely on the input of continuous images. However, it is very complicated for the odometry network to learn the epipolar geometry information provided by the images.
Yanzi Miao +6 more
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Real-Time Vehicle Positioning and Mapping Using Graph Optimization
Sensors, 2021 In this work, we propose and evaluate a pose-graph optimization-based real-time multi-sensor fusion framework for vehicle positioning using low-cost automotive-grade sensors. Pose-graphs can model multiple absolute and relative vehicle positioning sensor
Anweshan Das +2 more
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Deep Visual Odometry With Adaptive Memory [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 accepted to TPAMI and an extension of CVPR oral paper: Beyond Tracking: Selecting Memeory and Refining Poses for Deep Visual Ododmetry.
Fei Xue +3 more
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Hybrid-Residual-Based RGBD Visual Odometry
IEEE Access, 2018 Visual odometry has greatly progressed since non-linear optimization methods were introduced for pose estimation. Furthermore, RGBD visual odometry has become a hot research topic in the robotic and computer vision field with the introduction of RGBD ...
Qinghua Yu +3 more
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Event-Based Stereo Visual Odometry [PDF]
IEEE Transactions on Robotics, 2021 Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. Their advantages make it possible to tackle challenging scenarios in robotics, such as high-speed and high dynamic range scenes. We present a solution to the problem of visual
Yi Zhou 0010 +2 more
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IEEE Robotics & Automation Magazine, 2011 Visual odometry (VO) is the process of estimating the egomotion of an agent (e.g., vehicle, human, and robot) using only the input of a single or If multiple cameras attached to it. Application domains include robotics, wearable computing, augmented reality, and automotive. The term VO was coined in 2004 by Nister in his landmark paper.
Davide Scaramuzza 0001 +1 more
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Semantic segmentation–aided visual odometry for urban autonomous driving
International Journal of Advanced Robotic Systems, 2017 Visual odometry plays an important role in urban autonomous driving cars. Feature-based visual odometry methods sample the candidates randomly from all available feature points, while alignment-based visual odometry methods take all pixels into account ...
Lifeng An +3 more
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AN AUTOMATIC KEY-FRAME SELECTION METHOD FOR VISUAL ODOMETRY BASED ON THE IMPROVED PWC-NET [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 In order to quick response to the rapid changes of mobile platforms in complex situations such as speedy changing direction or camera shake, visual odometry/visual simultaneous localization and mapping (VO/VSLAM) always needs a high frame rate vision ...
Y. Chen, L. Yan, X. Lin
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