Results 161 to 170 of about 8,729 (215)

Targetless Radar-Camera Calibration via Trajectory Alignment. [PDF]

Sensors (Basel)
Durmaz O, Cevikalp H.
europepmc   +1 more source

Edge-Point Cloud Fusion for Geometric Fitting of Cylinder Parameters Using Single-View RGB-D Data. [PDF]

Sensors (Basel)
Zhang H, Liu J, Wang Z.
europepmc   +1 more source

Vision and 2D LiDAR Fusion-Based Navigation Line Extraction for Autonomous Agricultural Robots in Dense Pomegranate Orchards. [PDF]

Sensors (Basel)
Shi Z, Bai Z, Yi K, Qiu B, Dong X, Wang Q, Jiang C, Zhang X, Huang X.   +8 more
europepmc   +1 more source

Road Marking Distress Detection and Assessment Based on UAV Imagery. [PDF]

Materials (Basel)
Nie Y, Wu W, Shan J, Peng H, Guo F, Liu Y, Xiao J.   +6 more
europepmc   +1 more source

AKAZE-GMS-PROSAC: A New Progressive Framework for Matching Dynamic Characteristics of Flotation Foam. [PDF]

J Imaging
Peng Z, Jiang Z, Zhu P, Cai G, Luo X.
europepmc   +1 more source

Gráf-vágás RANSAC

, 2019
openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

SC-RANSAC: Spatial consistency on RANSAC

Multimedia Tools and Applications, 2018
The goal of robust parameter estimation is developing a model which can properly fit to data. Parameter estimation of a geometric model, in presence of noise and error, is an important step in many image processing and computer vision applications. As the random sample consensus (RANSAC) algorithm is one of the most well-known algorithms in this field,
Shohreh Kasaei, Mehran Fotouhi
exaly   +2 more sources

Distributed RANSAC for 3D reconstruction

SPIE Proceedings, 2008
Many low or middle level 3D reconstruction algorithms involve a robust estimation and selection step by which parameters of the best model are estimated and inliers fitting this model are selected. The RANSAC algorithm is the most widely used robust algorithm for this step. However, this robust algorithm is computationally demanding.
Mai Xu, Maria Petrou
openaire   +2 more sources

Radar odometry with recursive-RANSAC

IEEE Transactions on Aerospace and Electronic Systems, 2016
This paper explores the use of radar odometry for Global Positioning System–denied navigation. The range progression from arbitrary ground-based point scatterers is used to estimate an unmanned aerial vehicle’s relative motion. In high clutter environments, the recursive-RANSAC algorithm provides robust and efficient feature identification, data ...
Eric B. Quist, Peter C. Niedfeldt, Randal W. Beard   +2 more
openaire   +1 more source