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Object‐aware deep feature extraction for feature matching [PDF]
Concurrency and Computation: Practice and Experience, 2023 SummaryFeature extraction is a fundamental step in the feature matching task. A lot of studies are devoted to feature extraction. Recent researches propose to extract features by pre‐trained neural networks, and the output is used for feature matching.
Zuoyong Li +4 more
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Feature Based Dynamic Matching
Proceedings of the 24th ACM Conference on Economics and Computation, 2023SOAR ing to Optimality: Smarter Matching Algorithms for On-Demand Platforms In “Feature-Based Dynamic Matching,” Y. Chen, Y. Kanoria, A. Kumar, and W. Zhang study dynamic two-sided matching where both customers and service providers are characterized by high-dimensional feature vectors, motivated by platforms like on-demand home ...
Yilun Chen +3 more
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View matching with blob features
Image and Vision Computing, 2005This paper introduces a new region based feature for object recognition and image matching. In contrast to many other region based features, this one makes use of colour in the feature extraction stage. We perform experiments on the repeatability rate of the features across scale and inclination angle changes, and show that avoiding to merge regions ...
Per-Erik Forssén, Anders Moe
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XAI Feature Detector for Ultrasound Feature Matching
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021Feature matching is a crucial component of computer vision that has various applications. With the emergence of Computer-Aided Diagnosis (CAD), the need for feature matching has also emerged in the medical imaging field. In this paper, we proposed a novel algorithm using the Explainable Artificial Intelligence (XAI) [1] approach to achieve feature ...
Zihao Wang +3 more
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Feature extraction and terrain matching
Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 2003An 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 +2 more
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Progressive Filtering for Feature Matching
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019In 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 +2 more
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Feature recognition by template matching
Computers & Graphics, 2000Abstract 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
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Deep Semantic Feature Matching
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017Estimating dense visual correspondences between objects with intra-class variation, deformations and background clutter remains a challenging problem. Thanks to the breakthrough of CNNs there are new powerful features available. Despite their easy accessibility and great success, existing semantic flow methods could not significantly benefit from these
Nikolai Ufer, Björn Ommer
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Feature matching in growing databases
2012 19th IEEE International Conference on Image Processing, 2012As 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 +1 more
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Detecting and matching feature points
Journal of Visual Communication and Image Representation, 2005Abstract This paper proposes a new feature point detector which uses a wedge model to characterize corners by their orientation and angular width. This detector is compared to two popular feature point detectors: the Harris and SUSAN detectors, on the basis of some defined quality attributes.
Étienne Vincent, Robert Laganière
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