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  • CNN for IMU assisted odometry estimation using

    2018-4-27 · Together with IMU support, high quality odometry estimation and LiDAR data registration is realized. Moreover, we propose alternative CNNs trained for the prediction of rotational motion parameters while achieving results also comparable with state of the art.

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  • [2005.02042] SROM: Simple Real-time Odometry

    2020-5-6 · Our SLAM system can build reliable maps at the same time generating high-quality odometry. We exhaustively evaluated the proposed method in many challenging highways/country/urban sequences from the KITTI dataset and the results demonstrate better accuracy in comparisons to other state-of-the-art methods with reduced computational expense aiding in real-time realizations.

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  • Estimating Visual Odometry with Prerecorded

    2021-1-22 · The KITTI Vision Benchmark Suite is a high-quality dataset to benchmark and compare various computer vision algorithms. Among other options, the KITTI dataset has sequences for evaluating stereo visual odometry. To get the KITTI test sequences, download the odometry …

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  • Deep Direct Visual Odometry | DeepAI

    2019-12-11 · Monocular direct visual odometry (DVO) relies heavily on high-quality images and good initial pose estimation for accuracy tracking process, which means that DVO may fail if the image quality is poor or the initial value is incorrect.

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  • [1912.05101] Deep Direct Visual Odometry - arXiv

    2019-12-11 · Monocular direct visual odometry (DVO) relies heavily on high-quality images and good initial pose estimation for accuracy tracking process, which means that DVO may fail if the image quality is poor or the initial value is incorrect. In this study, we present a new architecture to overcome the above limitations by embedding deep learning into DVO.

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  • GitHub - Kapernikov/zed_visual_odometry: Guide

    2021-7-7 · To start, we will use an example of a robot with wheel encoders as its odometry source. Note that wheel encoders are not required for Nav2 but it is common in most setups. The goal in setting up the odometry is to compute the odometry information and publish the nav_msgs/Odometry message and odom => base_link transform over ROS2. To calculate this information, you will need to setup some code that will translate wheel encoder information into odometry …

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  • Setting Up Odometry — Navigation 2 1.0.0

    2019-12-1 · Monocular direct visual odometry (DVO) relies heavily on high-quality images and good initial pose estimation for accuracy tracking process, which means that DVO may fail if the image quality is poor or the initial value is incorrect. In this study, we present a new architecture to overcome the above limitations by embedding deep learning into DVO.

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  • Deep Direct Visual Odometry - NASA/ADS

    2014-8-16 · Visual Odometry (VO) After all, it's what nature uses, too! Cellphone processor unit 1.7GHz quadcore ARM <10g Cellphone type camera, up to 16Mp (480MB/s @ …

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  • Visual Odometry

    2020-12-30 · In this paper, we propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The optimization is achieved by exploiting the photometric response function of the camera.

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  • Deep Direct Visual Odometry | DeepAI

    2019-12-11 · Deep Direct Visual Odometry. 12/11/2019 ∙ by Chaoqiang Zhao, et al. ∙ East China Universtiy of Science and Technology ∙ 0 ∙ share . Monocular direct visual odometry (DVO) relies heavily on high-quality images and good initial pose estimation for accuracy tracking process, which means that DVO may fail if the image quality is poor or the initial value is incorrect.

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  • Visual Odometry - an overview | ScienceDirect Topics

    Visual Odometry (VO) algorithms (Nister, Naroditsky, & Bergen, 2004; Scaramuzza & Fraundorfer, 2011) handle the problem of estimating the 3D position and orientation of the vehicle. The estimation process performs sequential analysis (frame after frame) of the captured scene; to recover the pose of the vehicle.

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  • Visual Odometry with the zed stereo camera –

    2021-3-12 · sensors can provide high-quality data. The weaknesses are also obviously, the results are sensitive to the data quality and it is also easy to converge to the suboptimal solutions once there are not enough constraints. When considering the loosely coupled fusion, Kalman filter is the most popular one among various solutions. There are

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  • Stereo Visual-Inertial Odometry With Multiple Kalman ...

    2020-12-30 · In this paper, we propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The optimization is achieved by exploiting the photometric response function of the camera.

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  • Robot Perception Group - UZH

    2016-7-25 · In this work, a) we propose a method to carefully sample high-quality correspondences from deep flows and recover accurate camera poses with a geometric module; b) we address the scale-drift issue by aligning geometrically triangulated depths to the scale

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  • LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with ...

    2020-8-17 · Multi-sensor fusion of multi-modal measurements from commodity inertial, visual and LiDAR sensors to provide robust and accurate 6DOF pose estimation holds great potential in robotics and beyond. In this paper, building upon our prior work (i.e., LIC-Fusion), we develop a sliding-window filter based LiDAR-Inertial-Camera odometry with online spatiotemporal calibration (i.e., LIC-Fusion 2.0 ...

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  • GitHub - BTREE-C802/3DLine-SLAM: 3DLines-SLAM: A

    2018-10-12 · High-quality Textured 3D Shape Reconstruction with Cascaded Fully Convolutional Networks IEEE Transactions on Visualization and Computer Graphics, 2021, Vol. 27, No.1, 83-97. Zheng-Ning Liu, Yan-Pei Cao, Zheng-Fei Kuang, Leif Kobbelt, Shi-Min Hu

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  • IMU-Aided High-Frequency Lidar Odometry for

    2019-4-11 · IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving Hanzhang Xue 1, ... high-frequency localization results in diverse environment without any prior information. ... signal is unavailable or is of poor quality. Currently, most autonomous vehicles are equipped with light detection and ranging (lidar)

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  • Robust Stereo Visual-Inertial Odometry Using

    The fusion of visual and inertial odometry has matured greatly due to the complementarity of the two sensors. However, the use of high-quality sensors and powerful processors in some applications is difficult due to size and cost limitations, and there are also many challenges in terms of robustness of the algorithm and computational efficiency.

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  • Trifo-VIO: Robust and Efficient Stereo Visual Inertial ...

    2021-4-26 · Odometry (Trifo-VIO), a tightly-coupled filtering-based stereo VIO system using both points and lines. Line features help ... Ironsides dataset, a new visual-inertial dataset, featuring high-quality synchronized stereo camera and IMU data from the Ironsides sensor [3] with various motion types and textures and millimeter-accuracy groundtruth ...

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  • Deep Direct Visual Odometry - NASA/ADS

    Monocular direct visual odometry (DVO) relies heavily on high-quality images and good initial pose estimation for accuracy tracking process, which means that DVO may fail if the image quality is poor or the initial value is incorrect. In this study, we present a new architecture to overcome the above limitations by embedding deep learning into DVO. A novel self-supervised network architecture ...

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  • LIC-Fusion: LiDAR-Inertial-Camera Odometry

    2020-5-1 · visual odometry (VO) and LiDAR odometry which uses high-frequency visual odometry to estimate the overall ego-motion while lower-rate LiDAR odometry, which matches scans to the map and refines the VO estimates. Shin, Park, and Kim [15] have used the depth from LiDAR in a di-rect visual SLAM method, where photometric errors were

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  • GR-LOAM: LiDAR-based sensor fusion SLAM for

    2016-7-25 · In this work, a) we propose a method to carefully sample high-quality correspondences from deep flows and recover accurate camera poses with a geometric module; b) we address the scale-drift issue by aligning geometrically triangulated depths to the scale

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  • Apple Developer Documentation

    2021-6-1 · Download : Download high-res image (674KB) Download : Download full-size image Fig. 3. Pipeline of proposed GR-LOAM. The system starts with measurement data synchronization and preprocessing. The GR-odometry thread tightly couples LiDAR cloud points, pre-integrated IMU and encoder data, and ground constraints to optimize the robot pose variation in a local window and provide high …

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  • Lu Sheng's Homepage

    To build high-quality AR experiences, be aware of these caveats and tips. Design AR experiences for predictable lighting conditions. World tracking involves image analysis, which requires a clear image. Tracking quality is reduced when the camera can’t see details, such as when the camera is pointed at a blank wall or the scene is too dark.

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  • Robust Stereo Visual-Inertial Odometry Using

    The fusion of visual and inertial odometry has matured greatly due to the complementarity of the two sensors. However, the use of high-quality sensors and powerful processors in some applications is difficult due to size and cost limitations, and there are also many challenges in terms of robustness of the algorithm and computational efficiency.

    Get Price
  • The TUM VI Benchmark for Evaluating Visual-Inertial

    2020-3-9 · of the topic of visual-inertial odometry, the availability of high-quality datasets is surprisingly small. Compared to single-camera, purely visual datasets, the challenge with a stereo visual-intertial dataset lies in the accurate synchroniza-tion of three sensors. A commonly used option for evaluating

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  • Deep Direct Visual Odometry - NASA/ADS

    Monocular direct visual odometry (DVO) relies heavily on high-quality images and good initial pose estimation for accuracy tracking process, which means that DVO may fail if the image quality is poor or the initial value is incorrect. In this study, we present a new architecture to overcome the above limitations by embedding deep learning into DVO. A novel self-supervised network architecture ...

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  • ADVIO: An Authentic Dataset for Visual-Inertial Odometry

    2018-8-28 · puter vision benchmark sets for visual-inertial odometry. For this pur-pose, we have built a test rig equipped with an iPhone, a Google Pixel Android phone, and a Google Tango device. We provide a wide range of raw sensor data that is accessible on almost any modern-day smartphone together with a high-quality ground-truth track. We also compare ...

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  • Events-To-Video: Bringing Modern Computer Vision to

    2019-6-10 · Object classification Visual-inertial odometry Off-the-shelf algorithm Figure 1. Our network converts a spatio-temporal stream of events (left) into a high-quality video (right). This enables direct ap-plication of off-the-shelf computer vision algorithms such as ob-ject classification (Section 5.1) and visual-inertial odometry (Sec-

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  • Visual-inertial odometry algorithms on the base of

    2019-7-25 · To check the quality of the developed algorithms for visual inertial odometry, a full-scale survey was conducted from a hydroplane using two cameras, an IR and a visible range. As the infrared camera used camera thermal range COX 1000 with a resolution of 1024 * 768. A suspension was made for the field survey (Figure 2).

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  • Comparison of Three Off-the-Shelf Visual Odometry

    Positioning is an essential aspect of robot navigation, and visual odometry an important technique for continuous updating the internal information about robot position, especially indoors without GPS (Global Positioning System). Visual odometry is using one or more cameras to find visual clues and estimate robot movements in 3D relatively. Recent progress has been made, especially with fully ...

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  • The KITTI Vision Benchmark Suite - Cvlibs

    The Rawseeds Project: Indoor and outdoor datasets with GPS, odometry, stereo, omnicam and laser measurements for visual, laser-based, omnidirectional, sonar and multi-sensor SLAM evaluation. Victoria Park Sequence: Widely used sequence for evaluating laser-based SLAM. Trees serve as landmarks, detection code is included.

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  • Dataset - Valeo

    Dataset. WoodScape comprises four surround-view cameras and nine tasks, including segmentation, depth estimation, 3D bounding box detection, and a novel soiling detection. Semantic annotation of 40+ classes at the instance level is provided for over 10,000 images. With WoodScape, we would like to encourage the community to adapt computer vision ...

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  • Super Odometry: IMU-centric LiDAR-Visual-Inertial ...

    2021-4-30 · Super Odometry: IMU-centric LiDAR-Visual-Inertial Estimator for Challenging Environments. We propose Super Odometry, a high-precision multi-modal sensor fusion framework, providing a simple but effective way to fuse multiple sensors such as LiDAR, camera, and IMU sensors and achieve robust state estimation in perceptually-degraded environments.

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  • TP-TIO: A Robust Thermal-Inertial Odometry with Deep ...

    2020-10-22 · odometry and proved the effectiveness of the direct method. However, since the direct methods heavily rely on image quality and accurate initial pose from the back-end module, it is particularly challenging for these methods to provide robust motion estimation when the environments have a scarcity of thermal gradients. In contrast, since our ...

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  • Robust Real-Time Visual Odometry for Dense RGB-D

    2014-1-18 · D odometry algorithm allowing real-time operation within the Kintinuous framework. Following that in Section V we describe the combination of various odometry estimation algorithms and a method for combining the dense ICP and RGB-D odometry estimators to produce an estimator which makes use of both dense depth and photometric information. IV.

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  • Poisson Surface Reconstruction for LiDAR Odometry and

    2021-3-25 · odometry and mapping, focusing on improving the mapping quality and at the same time estimating the pose of the vehicle. Our approach performs frame-to-mesh ICP, but in contrast to other SLAM approaches, we represent the map as a triangle mesh computed via Poisson surface reconstruction. We perform

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  • Comparison of Three Off-the-Shelf Visual Odometry

    Positioning is an essential aspect of robot navigation, and visual odometry an important technique for continuous updating the internal information about robot position, especially indoors without GPS (Global Positioning System). Visual odometry is using one or more cameras to find visual clues and estimate robot movements in 3D relatively. Recent progress has been made, especially with fully ...

    Get Price
  • Opportunity rover localization and topographic

    The Rawseeds Project: Indoor and outdoor datasets with GPS, odometry, stereo, omnicam and laser measurements for visual, laser-based, omnidirectional, sonar and multi-sensor SLAM evaluation. Victoria Park Sequence: Widely used sequence for evaluating laser-based SLAM. Trees serve as landmarks, detection code is included.

    Get Price
  • The KITTI Vision Benchmark Suite - Cvlibs

    Dataset. WoodScape comprises four surround-view cameras and nine tasks, including segmentation, depth estimation, 3D bounding box detection, and a novel soiling detection. Semantic annotation of 40+ classes at the instance level is provided for over 10,000 images. With WoodScape, we would like to encourage the community to adapt computer vision ...

    Get Price
  • Dataset - Valeo

    2019-3-5 · We propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The

    Get Price