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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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Object‐aware deep feature extraction for feature matching
Concurrency and Computation: Practice and Experience, 2023SummaryFeature 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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Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing, 2012
Computing the dense Approximate Nearest-Neighbour Field (ANNF) between a pair of images has become a major problem which is being tackled by the image processing community in the recent years. Two important papers viz. PatchMatch [3] and CSH [11] have been developed over the past few years based on the coherency between images, but one major problem ...
S. Avinash Ramakanth, R. Venkatesh Babu
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Computing the dense Approximate Nearest-Neighbour Field (ANNF) between a pair of images has become a major problem which is being tackled by the image processing community in the recent years. Two important papers viz. PatchMatch [3] and CSH [11] have been developed over the past few years based on the coherency between images, but one major problem ...
S. Avinash Ramakanth, R. Venkatesh Babu
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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 +3 more
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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 +3 more
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Matching Images Using Linear Features
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984We describe techniques for matching two images or an image and a map. This operation is basic for machine vision and is needed for the tasks of object recognition, change detection, map up-dating, passive navigation, and other tasks. Our system uses line-based descriptions, and matching is accomplished by a relaxation operation which computes most ...
G, Medioni, R, Nevatia
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Feature Matching with Bounded Distortion
ACM Transactions on Graphics, 2014We consider the problem of finding a geometrically consistent set of point matches between two images. We assume that local descriptors have provided a set of candidate matches, which may include many outliers. We then seek the largest subset of these correspondences that can be aligned perfectly using a nonrigid deformation that exerts a bounded ...
Lipman, Yaron +4 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 ...
P.-E. Forssen, A. Moe
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Feature vector field and feature matching
Pattern Recognition, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, F. C., Wang, Z. H., Wang, X. G.
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FEATURE GROUP MATCHING: A NOVEL METHOD TO FILTER OUT INCORRECT LOCAL FEATURE MATCHINGS
International Journal of Pattern Recognition and Artificial Intelligence, 2014The importance of finding correct correspondences between two images is the major aspect in problems such as appearance-based robot localization and content-based image retrieval. Local feature matching has become a commonly used method to compare images, despite being highly probable that at least some of the matchings/correspondences it detects are ...
FRONTONI, EMANUELE +2 more
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Line feature matching algorithm
SPIE Proceedings, 2007This paper presents a line feature matching algorithm. Firstly, it extracts the set of line features in the image, and represents an object using attributed relational graph (ARG). By defining relation vectors between the adjacent features, the graph can describe the structural information of an object.
Taisong Jin, Cuihua Li
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