Results 301 to 310 of about 3,367,886 (347)

Detecting and matching feature points

Journal of Visual Communication and Image Representation, 2005
Abstract 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
openaire   +1 more source

Deep Semantic Feature Matching

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Estimating 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
openaire   +1 more source

Feature Matching and Deep Learning Models for Attitude Estimation on a Micro-Aerial Vehicle

International Conference on Computing and Information, 2022
In today’s digital era, destructive and non-destructive methods of cyber-attacks are being exploited particularly for robotic applications. For this, artificial intelligence particularly in cybernetics plays a vital role.
Narumol Chumuang, A. Farooq, Muhammad Irfan, Sumair Aziz, Moomal Qureshi   +4 more
semanticscholar   +1 more source

End2End Multi-View Feature Matching with Differentiable Pose Optimization

IEEE International Conference on Computer Vision, 2022
Erroneous feature matches have severe impact on subsequent camera pose estimation and often require additional, time-costly measures, like RANSAC, for outlier rejection.
Barbara Roessle, M. Nießner
semanticscholar   +1 more source

Locality-Guided Global-Preserving Optimization for Robust Feature Matching

IEEE Transactions on Image Processing, 2022
Feature matching is a fundamental problem in many computer vision tasks. This paper proposes a novel effective framework for mismatch removal, named LOcality-guided Global-preserving Optimization (LOGO).
Yifan Xia, Jiayi Ma
semanticscholar   +1 more source

Single image super-resolution based on trainable feature matching attention network

Pattern Recognition
Convolutional Neural Networks (CNNs) have been widely employed for image Super-Resolution (SR) in recent years. Various techniques enhance SR performance by altering CNN structures or incorporating improved self-attention mechanisms. Interestingly, these
Qizhou Chen, Qing Shao
semanticscholar   +1 more source

Comparison of Feature Detection and Matching Approaches: SIFT and SURF

Global Research and Development Journals
Feature detection and matching are used in image registration, object tracking, object retrieval etc. There are number of approaches used to detect and matching of features as SIFT (Scale Invariant Feature Transform), SURF (Speeded up Robust Feature ...
D. Mistry, A. Banerjee
semanticscholar   +1 more source

Robust Feature Matching for Remote Sensing Image Registration via Linear Adaptive Filtering

IEEE Transactions on Geoscience and Remote Sensing, 2021
As a fundamental and critical task in feature-based remote sensing image registration, feature matching refers to establishing reliable point correspondences from two images of the same scene.
Xingyu Jiang, Jiayi Ma, Aoxiang Fan, Haiping Xu, Geng Lin, Tao Lu, Xin Tian   +6 more
semanticscholar   +1 more source

Feature Detection and Matching

2010
Feature detection and matching are an essential component of many computer vision applications. Consider the two pairs of images shown in Figure 4.2. For the first pair, we may wish to align the two images so that they can be seamlessly stitched into a composite mosaic (Chapter 9).
openaire   +1 more source

FEATURE GROUP MATCHING: A NOVEL METHOD TO FILTER OUT INCORRECT LOCAL FEATURE MATCHINGS

International Journal of Pattern Recognition and Artificial Intelligence, 2014
The 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 ...
Emanuele Frontoni, Adriano Mancini, Primo Zingaretti   +2 more
openaire   +1 more source