Results 291 to 300 of about 3,367,886 (347)

LNIFT: Locally Normalized Image for Rotation Invariant Multimodal Feature Matching

IEEE Transactions on Geoscience and Remote Sensing, 2022
Severe nonlinear radiation distortion (NRD) is the bottleneck problem of multimodal image matching. Although many efforts have been made in the past few years, such as the radiation-variation insensitive feature transform (RIFT) and the histogram of ...
Jiayuan Li, Wang Xu, Pengcheng Shi, Yongjun Zhang, Qingwu Hu   +4 more
semanticscholar   +1 more source

OAMatcher: An Overlapping Areas-based Network for Accurate Local Feature Matching

Pattern Recognition, 2023
Local feature matching is an essential component in many visual applications. In this work, we propose OAMatcher, a Tranformer-based detector-free method that imitates humans behavior to generate dense and accurate matches.
Kun Dai, Tao Xie, K. Wang, Zhiqiang Jiang, Ruifeng Li, Lijun Zhao   +5 more
semanticscholar   +1 more source

Feature extraction and terrain matching

Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 2003
An algorithm is presented which uses Gaussian curvature for extracting special points on the terrain, and then uses these points for recognition of particular regions of the terrain. The Gaussian curvature is chosen because it is invariant under isometry, which includes rotation and translation.
Dmitry B. Goldgof, Thomas S. Huang, Hua Lee   +2 more
openaire   +1 more source

Progressive Filtering for Feature Matching

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
In this paper, we propose a simple yet efficient method termed as Progressive Filtering for Feature Matching, which is able to establish accurate correspondences between two images of common or similar scenes. Our algorithm first grids the correspondence space and calculates a typical motion vector for each cell, and then removes false matches by ...
Xingyu Jiang, Jiayi Ma 0001, Jun Chen 0019   +2 more
openaire   +1 more source

Feature recognition by template matching

Computers & Graphics, 2000
Abstract Most existing techniques in feature recognition are limited to the recognition of “regular” shape features such as hole, slot, pocket, etc. which are commonly used in mechanical CAD/CAM applications. This research tackles the problem of free-from features recognition.
C. L. Li, Kin Chuen Hui
openaire   +1 more source

Feature matching in growing databases

2012 19th IEEE International Conference on Image Processing, 2012
As feature-based image matching is applied to increasing larger scale problems, it becomes necessary to match features across increasingly larger databases. Current approaches are able to conduct such feature matching, but are not flexible enough to be applied to databases that may grow at runtime.
Bernardo Rodrigues Pires, José M. F. Moura   +1 more
openaire   +1 more source

JamMa: Ultra-lightweight Local Feature Matching with Joint Mamba

Computer Vision and Pattern Recognition
Existing state-of-the-art feature matchers capture long-range dependencies with Transformers but are hindered by high spatial complexity, leading to demanding training and high-latency inference.
Xiaoyong Lu, Songlin Du
semanticscholar   +1 more source

Robust feature matching in 2.3µs

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2009
In this paper we present a robust feature matching scheme in which features can be matched in 2.3µs. For a typical task involving 150 features per image, this results in a processing time of 500µs for feature extraction and matching. In order to achieve very fast matching we use simple features based on histograms of pixel intensities and an indexing ...
Simon Taylor, Edward Rosten, Tom Drummond   +2 more
openaire   +1 more source

Feature Matching of Images

2021 6th International Conference for Convergence in Technology (I2CT), 2021
SIFT method for the local description of images is introduced in this paper. After figuring out the various features of the images, this method is used to perform accurate comparison between different views of a scene or an object. The extracted characteristics are invariable to rotation of size, additional noise, change of light, cropped images ...
Shahid Eqbal, Aanchal Verna, Akanksha Soni, Ankit Kumar   +3 more
openaire   +1 more source

A Cloud Motion Estimation Method Based on Cloud Image Depth Feature Matching

IEEE Geoscience and Remote Sensing Letters
The movement of clouds directly influences fluctuations in solar radiation. Therefore, cloud motion vector (CMV) estimation techniques are widely applied in sequential cloud images to predict solar radiation and study other meteorologically related ...
Lianglin Zou, Ping Tang, Yisen Niu, Zixuan Yan, Xilong Lin, Jifeng Song, Qian Wang   +6 more
semanticscholar   +1 more source