Nothing Special   »   [go: up one dir, main page]

Peng et al., 2020 - Google Patents

Globally-optimal event camera motion estimation

Peng et al., 2020

View PDF
Document ID
7115143646675367391
Author
Peng X
Wang Y
Gao L
Kneip L
Publication year
Publication venue
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXVI 16

External Links

Snippet

Event cameras are bio-inspired sensors that perform well in HDR conditions and have high temporal resolution. However, different from traditional frame-based cameras, event cameras measure asynchronous pixel-level brightness changes and return them in a highly …
Continue reading at arxiv.org (PDF) (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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation 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
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • 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
    • 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
    • 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
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • 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
    • 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
    • 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
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0068—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for image registration, e.g. elastic snapping

Similar Documents

Publication Publication Date Title
Cheng et al. Improving monocular visual SLAM in dynamic environments: an optical-flow-based approach
US10096129B2 (en) Three-dimensional mapping of an environment
Taketomi et al. Visual SLAM algorithms: A survey from 2010 to 2016
Silveira et al. An efficient direct approach to visual SLAM
Alismail et al. Photometric bundle adjustment for vision-based slam
Peng et al. Globally-optimal event camera motion estimation
Eade et al. Edge landmarks in monocular SLAM
GB2541153A (en) Processing a series of images to identify at least a portion of an object
Kim et al. Planar structures from line correspondences in a manhattan world
Poddar et al. Motion estimation made easy: Evolution and trends in visual odometry
Belter et al. Modeling spatial uncertainty of point features in feature-based RGB-D SLAM
Guizilini et al. Semi-parametric learning for visual odometry
Liu et al. Accurate real-time visual SLAM combining building models and GPS for mobile robot
Wientapper et al. Composing the feature map retrieval process for robust and ready-to-use monocular tracking
Kovács et al. Saliency and spatial information-based landmark selection for mobile robot navigation in natural environments
Kniaz Real-time optical flow estimation on a GPU for a skied-steered mobile robot
Dong et al. Monocular visual-IMU odometry using multi-channel image patch exemplars
Sommer et al. Sf2se3: Clustering scene flow into se (3)-motions via proposal and selection
Kniaz Fast instantaneous center of rotation estimation algorithm for a skied-steered robot
Suri Pose constraints for consistent self-supervised monocular depth and ego-motion
Ahuja et al. Three‐dimensional Scan Registration using Curvelet Features in Planetary Environments
Sun et al. Scale‐aware camera localization in 3D LiDAR maps with a monocular visual odometry
Xia et al. YOLO-based semantic segmentation for dynamic removal in visual-inertial SLAM
Liwicki et al. Coarse-to-fine planar regularization for dense monocular depth estimation
Djordjevic et al. An accurate method for 3D object reconstruction from unordered sparse views