Results 161 to 170 of about 5,152 (205)

Geometry-Constrained Learning-Based Visual Servoing with Projective Homography-Derived Error Vector. [PDF]

Sensors (Basel)
Zhang Y, Ghosh A, An Y, Joo K, Kim S, Kuc T.   +5 more
europepmc   +1 more source

STN-Homography: Direct Estimation of Homography Parameters for Image Pairs [PDF]

Applied Sciences (Switzerland), 2019
Estimating a 2D homography from a pair of images is a fundamental task in computer vision. Contrary to most convolutional neural network-based homography estimation methods that use alternative four-point homography parameterization schemes, in this study, we directly estimate the 3 × 3 homography matrix value.
Qiang Zhou
exaly   +3 more sources

Self-Supervised deep homography estimation with invertibility constraints

Pattern Recognition Letters, 2019
Remarkable performance of the homography estimation has been achieved by the deep CNN based approaches. These homography estimation methods, more often than not, are supervised methods and rely too much on the ground truth annotations as they aim to ...
Xiao Bai, Chen Wang
exaly   +2 more sources

A Review of Homography Estimation: Advances and Challenges

Electronics (Switzerland), 2023
Images captured from different viewpoints or devices have often exhibited significant geometric and photometric differences due to factors such as environmental variations, camera technology differences, and shooting conditions’ instability.
Xingyi Wang, Yanhao Liao, Yinhui Luo
exaly   +2 more sources

Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model [PDF]

IEEE Robotics and Automation Letters, 2018
Homography estimation between multiple aerial images can provide relative pose estimation for collaborative autonomous exploration and monitoring. The usage on a robotic system requires a fast and robust homography estimation algorithm. In this study, we propose an unsupervised learning algorithm that trains a Deep Convolutional Neural Network to ...
Steven Chen, Ty Nguyen
exaly   +3 more sources

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Softferns for homography estimation

2011 18th IEEE International Conference on Image Processing, 2011
Ferns was recently proposed to address the problem of fast keypoint matching [1]. In estimating homography, it often yields many similar matching scores under large viewpoint change or when the object is highly repetitive. However, we observe that keypoints having similar scores are usually far away from each other.
Shaoguo Liu, Haibo Wang, Jixia Zhang, Franck Davoine, Chunhong Pan   +4 more
openaire   +1 more source

DMHomo: Learning Homography with Diffusion Models

ACM Transactions on Graphics
Supervised homography estimation methods face a challenge due to the lack of adequate labeled training data. To address this issue, we propose DMHomo, a diffusion model-based framework for supervised homography learning.
Bing Zeng, Ping Tan, Shuaicheng Liu
exaly   +2 more sources

The equivalence of two definitions of compatible homography matrices

Pattern Recognition Letters, 2020
In many computer vision applications, one acquires images of planar surfaces from two different vantage points. One can use a projective transformation to map pixel coordinates associated with a particular planar surface from one image to another.
Wojciech Chojnacki, Marten Wadenbäck, Zygmunt Szpak   +2 more
exaly   +2 more sources

Multiview constraints on homographies

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
The image motion of a planar surface between two camera views is captured by a homography (a 2D projective transformation). The homography depends on the intrinsic and extrinsic camera parameters, as well as on the 3D plane parameters. While camera parameters vary across different views, the plane geometry remains the same.
Lihi Zelnik-Manor, Michal Irani
openaire   +1 more source

Radial distortion homography

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
The importance of precise homography estimation is often underestimated even though it plays a crucial role in various vision applications such as plane or planarity detection, scene degeneracy tests, camera motion classification, image stitching, and many more.
Zuzana Kukelova, Jan Heller, Martin Bujnak, Tomás Pajdla   +3 more
openaire   +2 more sources