A Method to Enhance Homogeneous Distribution of Matched Features for Image Matching
International Journal of Environment and Geoinformatics, 2020 Features are distinctive landmarks of an image. There are various feature detection and description algorithms. Many computer vision algorithms require matching of features from two images.
Baran Gulmez +5 more
doaj +1 more source
ParaFormer: Parallel Attention Transformer for Efficient Feature Matching [PDF]
AAAI Conference on Artificial Intelligence, 2023 Heavy computation is a bottleneck limiting deep-learning-based feature matching algorithms to be applied in many real-time applications. However, existing lightweight networks optimized for Euclidean data cannot address classical feature matching tasks ...
Xiaoyong Lu +3 more
semanticscholar +1 more source
TopicFM: Robust and Interpretable Topic-Assisted Feature Matching [PDF]
AAAI Conference on Artificial Intelligence, 2022 This study addresses an image-matching problem in challenging cases, such as large scene variations or textureless scenes. To gain robustness to such situations, most previous studies have attempted to encode the global contexts of a scene via graph ...
Khang Truong Giang +2 more
semanticscholar +1 more source
FEATURE ANALYSIS FOR MULTI-WINDOW MATCHING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Image matching is a practical way to build up the relationship between point pairs. In remote sensing and photogrammetry applications, area-based matching algorithms are usually used under control environment, such as fixing exterior orientation ...
W. C. Chang, L. C. Chen
doaj +1 more source
BRIFT: A Binary Descriptor for Multi-Modal Image Registration [PDF]
Hangkong bingqi, 2023 Using radiation-variation insensitivity feature transform (RIFT) to calculate feature descriptors and perform feature matching on the maximum index map (MIM) is time-consuming.
Xu Kaikai, Guo Pengcheng, Wang Jingjing
doaj +1 more source
Learning Geometric Feature Embedding with Transformers for Image Matching
Sensors, 2022 Local feature matching is a part of many large vision tasks. Local feature matching usually consists of three parts: feature detection, description, and matching.
Xiaohu Nan, Lei Ding
doaj +1 more source
ASFM-Net: Asymmetrical Siamese Feature Matching Network for Point Completion [PDF]
ACM Multimedia, 2021 We tackle the problem of object completion from point clouds and propose a novel point cloud completion network employing an Asymmetrical Siamese Feature Matching strategy, termed as ASFM-Net.
Yaqi Xia +5 more
semanticscholar +1 more source
AdaSG: A Lightweight Feature Point Matching Method Using Adaptive Descriptor with GNN for VSLAM
Sensors, 2022 Feature point matching is a key component in visual simultaneous localization and mapping (VSLAM). Recently, the neural network has been employed in the feature point matching to improve matching performance.
Ye Liu +6 more
doaj +1 more source
Adaptive Assignment for Geometry Aware Local Feature Matching [PDF]
Computer Vision and Pattern Recognition, 2022 The detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance. However, these methods still struggle at large-scale and viewpoint variations, due to the geometric inconsistency resulting from
Dihe Huang +7 more
semanticscholar +1 more source
FedFM: Anchor-Based Feature Matching for Data Heterogeneity in Federated Learning [PDF]
IEEE Transactions on Signal Processing, 2022 One of the key challenges in federated learning (FL) is local data distribution heterogeneity across clients, which may cause inconsistent feature spaces across clients.
Rui Ye +5 more
semanticscholar +1 more source