Optical lens distortion correction method based on least square configuration

Zi-qing, 何子清 He; Guo-dong, 葛 超 Yu; Chunyang, 王春阳 Wang

doi:10.3788/yjyxs20193403.0302

Cited by 2 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Image deformation includes mainly radial and eccentric distortions. Previous research [40] has shown that the radial distortion is the main part of the optical distortion, while the eccentric distortion is only 1/7 to 1/8 of the radial distortion. Furthermore, when the radial distortion is eliminated, the influence of the eccentric distortion can also be alleviated, so the eccentric distortion can be ignored in the image calibration.…”

Section: The Preprocessing Methods Of Road Imagesmentioning

confidence: 94%

A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing

et al. 2023

View full text Add to dashboard Cite

In order to investigate the use of unmanned aerial vehicles (UAVs) for future application in road damage detection and to provide a theoretical and technical basis for UAV road damage detection, this paper determined the recommended flight and camera parameters based on the needs of continuous road image capture and pavement disease recognition. Furthermore, to realize automatic route planning and control, continuous photography control, and image stitching and smoothing tasks, a UAV control framework for road damage detection, based on the Dijkstra algorithm, the speeded-up robust features (SURF) algorithm, the random sampling consistency (RANSAC) algorithm, and the gradual in and out weight fusion method, was also proposed in this paper. With the Canny operator, it was verified that the road stitched long image obtained by the UAV control method proposed in this paper is applicable to machine learning pavement disease identification.

show abstract

Section: The Preprocessing Methods Of Road Imagesmentioning

confidence: 94%

A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing

et al. 2023

View full text Add to dashboard Cite

show abstract

Automatic Tracking Method of Basketball Flight Trajectory Based on Data Fusion and Sparse Representation Model

Chen¹,

Liu

2021

Complexity

View full text Add to dashboard Cite

The appearance model of flying basketball obtained by the traditional basketball flight trajectory tracking method is not accurate, which leads the anti-interference performance of trajectory tracking not ideal. Based on data fusion and sparse representation model, a new automatic trajectory tracking method is proposed. Firstly, the relevant technologies of basketball flight trajectory automatic tracking are studied and summarized, and then the method is studied. The specific implementation steps of this method are as follows: the features of flying basketball images were extracted by the target feature extraction algorithm, and the appearance model of flying basketball was built based on sparse representation. Data fusion technology and particle filter algorithm are combined to realize automatic tracking of basketball flight path. Through three axial basketball trajectories of automatic tracking test and noise test and verify the design method under the 3D world coordinate system to achieve the X, Y, and Z axis up more accurate tracking, at the same time, after applying measurement signal to noise, automatic trajectory tracking results affected by some, but still managed to realize the trajectory tracking.

show abstract

Optical lens distortion correction method based on least square configuration

Cited by 2 publications

References 0 publications

A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing

A Framework for Using UAVs to Detect Pavement Damage Based on Optimal Path Planning and Image Splicing

Automatic Tracking Method of Basketball Flight Trajectory Based on Data Fusion and Sparse Representation Model

Contact Info

Product

Resources

About