Feature-based pose estimation on-board MAVs equipped with 2D laser scanners for the automatic inspection of electric towers

2017 ◽  
Author(s):  
Carlos Vina ◽  
Pascal Morin
Keyword(s):  
Pose Estimation ◽  
Automatic Inspection ◽  
Laser Scanners ◽  
Feature Based

Perceptual feature-based object recognition for automatic inspection

1993 ◽  
Author(s):  
Gary P. Brown ◽  
Peter Forte ◽  
Ron Malyan ◽  
Peter Barnwell
Keyword(s):  
Object Recognition ◽  
Automatic Inspection ◽  
Perceptual Feature ◽  
Feature Based

scholarly journals Robust Object Pose Estimation From Feature-Based Stereo

2006 ◽  
Vol 55 (4) ◽  
pp. 1270-1280 ◽  
Author(s):  
R. Laganiere ◽  
S. Gilbert ◽  
G. Roth
Keyword(s):  
Pose Estimation ◽  
Feature Based ◽  
Object Pose Estimation

scholarly journals Pose Estimation of a Noncooperative Target Based on Monocular Visual SLAM

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Ting Lei ◽  
Xiao-Feng Liu ◽  
Guo-Ping Cai ◽  
Yun-Meng Liu ◽  
Pan Liu
Keyword(s):  
Pose Estimation ◽  
Large Scale ◽  
Direct Method ◽  
Estimation Methods ◽  
Current Frame ◽  
Feature Based ◽  
Simultaneous Location And Mapping ◽  
Slam Algorithm ◽  
Local Map ◽  
A Direct Method

This paper estimates the pose of a noncooperative space target utilizing a direct method of monocular visual simultaneous location and mapping (SLAM). A Large Scale Direct SLAM (LSD-SLAM) algorithm for pose estimation based on photometric residual of pixel intensities is provided to overcome the limitation of existing feature-based on-orbit pose estimation methods. Firstly, new sequence images of the on-orbit target are continuously inputted, and the pose of each current frame is calculated according to minimizing the photometric residual of pixel intensities. Secondly, frames are distinguished as keyframes or normal frames according to the pose relationship, and these frames are used to optimize the local map points. After that, the optimized local map points are added to the back-end map. Finally, the poses of keyframes are further enumerated and optimized in the back-end thread based on the map points and the photometric residual between the keyframes. Numerical simulations and experiments are carried out to prove the validity of the proposed algorithm, and the results elucidate the effectiveness of the algorithm in estimating the pose of the noncooperative target.

scholarly journals Depth Estimation of a Deformable Object via a Monocular Camera

2019 ◽  
Vol 9 (7) ◽  
pp. 1366 ◽  
Author(s):  
Guolai Jiang ◽  
Shaokun Jin ◽  
Yongsheng Ou ◽  
Shoujun Zhou
Keyword(s):  
Pose Estimation ◽  
A Priori ◽  
Depth Estimation ◽  
Target Object ◽  
Estimation Accuracy ◽  
Single Camera ◽  
Deformable Object ◽  
Nao Robot ◽  
Feature Based ◽  
Monocular Image

The depth estimation of the 3D deformable object has become increasingly crucial to various intelligent applications. In this paper, we propose a feature-based approach for accurate depth estimation of a deformable 3D object with a single camera, which reduces the problem of depth estimation to a pose estimation problem. The proposed method needs to reconstruct the target object at the very beginning. With the 3D reconstruction as an a priori model, only one monocular image is required afterwards to estimate the target object’s depth accurately, regardless of pose changes or deformability of the object. Experiments are taken on an NAO robot and a human to evaluate the depth estimation accuracy by the proposed method.

Feature-Based Pose Estimation

2011 ◽  
pp. 225-251 ◽  
Author(s):  
Cristian Sminchisescu ◽  
Liefeng Bo ◽  
Catalin Ionescu ◽  
Atul Kanaujia
Keyword(s):  
Pose Estimation ◽  
Feature Based
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