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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, Bjorn Ommer
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Feature Matching and Deep Learning Models for Attitude Estimation on a Micro-Aerial Vehicle
International Conference on Computing and Information, 2022In 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 +4 more
semanticscholar +1 more source
LSV-ANet: Deep Learning on Local Structure Visualization for Feature Matching
IEEE Transactions on Geoscience and Remote Sensing, 2022Feature matching is a fundamental and important task in many applications of remote sensing and photogrammetry. Remote sensing images often involve complex spatial relationships due to the ground relief variations and imaging viewpoint changes. Therefore,
Jiaxuan Chen +6 more
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Multi-Stage Refinement Feature Matching Using Adaptive ORB Features for Robotic Vision Navigation
IEEE Sensors Journal, 2022Feature matching is a crucial technique to estimate robot pose in the light of natural landmarks for a vision navigation system. It is difficult for the present feature matching approaches to balance the accuracy, robustness and efficiency for a vision ...
Chao Sun +4 more
semanticscholar +1 more source
Feature Point Matching with Matching Distribution
2015Most of the feature point matching techniques considers only the number of matches. The higher number of matches is, the better results are. However, reliability and quality of the matching is addressed in a few techniques. So, finding the good matches of the pairs of points from the two given point sets is one of the main issue of feature point ...
San Ratanasanya +2 more
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Generalized feature extraction using expansion matching
IEEE Transactions on Image Processing, 1999A novel generalized feature extraction method based on the expansion matching (EXM) method and on the Karhunen-Loeve transform (KLT) is presented. The method provides an efficient way to locate complex features of interest like corners and junctions with reduced number of filtering operations.
D, Nandy, J, Ben-Arie
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Reconstructing shredded documents through feature matching
Forensic Science International, 2006We describe a procedure for reconstructing documents that have been shredded by hand, a problem that often arises in forensics. The proposed method first applies a polygonal approximation in order to reduce the complexity of the boundaries and then extracts relevant features of the polygon to carry out the local reconstruction. In this way, the overall
Edson, Justino +2 more
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Feature Detection and Matching
2010Feature 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).
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Robust Feature Matching Using Spatial Clustering With Heavy Outliers
IEEE Transactions on Image Processing, 2020This paper focuses on removing mismatches from given putative feature matches created typically based on descriptor similarity. To achieve this goal, existing attempts usually involve estimating the image transformation under a geometrical constraint ...
Xingyu Jiang +3 more
semanticscholar +1 more source
2012
In many visual effects applications, we need to relate images taken from different perspectives or at different times. For example, we often want to track a point on a set as a camera moves around during a shot so that a digital creature can be later inserted at that location.
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In many visual effects applications, we need to relate images taken from different perspectives or at different times. For example, we often want to track a point on a set as a camera moves around during a shot so that a digital creature can be later inserted at that location.
openaire +1 more source