[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Jung et al., 2021 - Google Patents

Uncertainty-aware fast curb detection using convolutional networks in point clouds

Jung et al., 2021

Document ID
16500122166957628876
Author
Jung Y
Jeon M
Kim C
Seo S
Kim S
Publication year
Publication venue
2021 IEEE International Conference on Robotics and Automation (ICRA)

External Links

Snippet

Curb detection is an essential function of autonomous vehicles in urban areas. However, curbs are difficult to detect in complex urban environments in which many dynamic objects exist. Additionally, curbs appear in a variety of shapes and sizes. Previous studies have …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05—Geographic models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations

Similar Documents

Publication Publication Date Title
Jiang et al. Rellis-3d dataset: Data, benchmarks and analysis
Ma et al. Exploiting sparse semantic HD maps for self-driving vehicle localization
Behl et al. Pointflownet: Learning representations for rigid motion estimation from point clouds
Shinzato et al. Road terrain detection: Avoiding common obstacle detection assumptions using sensor fusion
Jung et al. Uncertainty-aware fast curb detection using convolutional networks in point clouds
Chen et al. 3d point cloud processing and learning for autonomous driving
Cappelle et al. Virtual 3D city model for navigation in urban areas
Zhao et al. Lidar mapping optimization based on lightweight semantic segmentation
Fernandes et al. Road detection using high resolution lidar
Murali et al. Utilizing semantic visual landmarks for precise vehicle navigation
Li et al. Robust localization for intelligent vehicles based on pole-like features using the point cloud
Dawood et al. Harris, SIFT and SURF features comparison for vehicle localization based on virtual 3D model and camera
Daraei et al. Velocity and shape from tightly-coupled LiDAR and camera
Suleymanov et al. Inferring road boundaries through and despite traffic
Dimitrievski et al. Robust matching of occupancy maps for odometry in autonomous vehicles
Charroud et al. Fast and accurate localization and mapping method for self-driving vehicles based on a modified clustering particle filter
Lyrio et al. Image-based mapping, global localization and position tracking using VG-RAM weightless neural networks
Wang et al. 3D-LIDAR based branch estimation and intersection location for autonomous vehicles
Wu Fusion-based modeling of an intelligent algorithm for enhanced object detection using a Deep Learning Approach on radar and camera data
Jung et al. Fast point clouds upsampling with uncertainty quantification for autonomous vehicles
Lin et al. Point cloud change detection with stereo V-SLAM: dataset, metrics and baseline
Can et al. Online lane graph extraction from onboard video
CN113505834A (en) Method for training detection model, determining image updating information and updating high-precision map
Li et al. Lane detection (part i): Mono-vision based method
Hyeon et al. KR-Net: A dependable visual kidnap recovery network for indoor spaces