Knorr et al., 2013 - Google Patents
Online extrinsic multi-camera calibration using ground plane induced homographiesKnorr et al., 2013
- Document ID
- 4805335140688599969
- Author
- Knorr M
- Niehsen W
- Stiller C
- Publication year
- Publication venue
- 2013 IEEE Intelligent Vehicles Symposium (IV)
External Links
Snippet
This paper presents an approach for online estimation of the extrinsic calibration parameters of a multi-camera rig. Given a coarse initial estimate of the parameters, the relative poses between cameras are refined through recursive filtering. The approach is purely vision …
- 230000000694 effects 0 abstract description 7
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
- G06T2207/10016—Video; Image sequence
-
- 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
- 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
- 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
- G06K9/62—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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Knorr et al. | Online extrinsic multi-camera calibration using ground plane induced homographies | |
Caruso et al. | Large-scale direct SLAM for omnidirectional cameras | |
Taguchi et al. | Point-plane SLAM for hand-held 3D sensors | |
Koide et al. | General, single-shot, target-less, and automatic lidar-camera extrinsic calibration toolbox | |
Bazin et al. | Motion estimation by decoupling rotation and translation in catadioptric vision | |
WO2018152214A1 (en) | Event-based feature tracking | |
Meier et al. | Visual‐inertial curve simultaneous localization and mapping: Creating a sparse structured world without feature points | |
Flores et al. | Efficient probability-oriented feature matching using wide field-of-view imaging | |
Fan et al. | Large-scale dense mapping system based on visual-inertial odometry and densely connected U-Net | |
Ahmadi et al. | HDPV-SLAM: Hybrid depth-augmented panoramic visual SLAM for mobile mapping system with tilted LiDAR and panoramic visual camera | |
Paudel et al. | 2D-3D camera fusion for visual odometry in outdoor environments | |
Gaspar et al. | New depth from focus filters in active monocular vision systems for indoor 3-D tracking | |
Luong et al. | Consistent ICP for the registration of sparse and inhomogeneous point clouds | |
He et al. | Three-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint | |
Hoang et al. | Combining edge and one-point ransac algorithm to estimate visual odometry | |
Zeng et al. | Fast and Robust Semi-Direct Monocular Visual-Inertial Odometry for UAV | |
Bunschoten et al. | 3D scene reconstruction from cylindrical panoramic images | |
Miksch et al. | Automatic extrinsic camera self-calibration based on homography and epipolar geometry | |
Chen et al. | 3d map building based on stereo vision | |
Saeedi et al. | 3D localization and tracking in unknown environments | |
Knorr | Self-Calibration of Multi-Camera Systems for Vehicle Surround Sensing | |
Shi et al. | Dynam-LVIO: A Dynamic-Object-Aware LiDAR Visual Inertial Odometry in Dynamic Urban Environments | |
Munguía et al. | Method for SLAM Based on Omnidirectional Vision: A Delayed‐EKF Approach | |
Pagel | Robust monocular egomotion estimation based on an iekf | |
Thapa et al. | A review on visual odometry techniques for mobile robots: Types and challenges |