Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
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TLDR
This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.Abstract:
This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also describes an approach to using these features for object recognition. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm, followed by a Hough transform to identify clusters belonging to a single object, and finally performing verification through least-squares solution for consistent pose parameters. This approach to recognition can robustly identify objects among clutter and occlusion while achieving near real-time performance.read more
Citations
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Proceedings ArticleDOI
Geometric Loss Functions for Camera Pose Regression with Deep Learning
Alex Kendall,Roberto Cipolla +1 more
TL;DR: In this article, the authors explore a number of novel loss functions for learning camera pose which are based on geometry and scene reprojection error, and show how to automatically learn an optimal weighting to simultaneously regress position and orientation.
Journal ArticleDOI
Evaluation of Features Detectors and Descriptors based on 3D Objects
Pierre Moreels,Pietro Perona +1 more
TL;DR: A method is designed, based on intersecting epipolar constraints, for providing ground truth correspondence automatically, which is based purely on geometric information, and does not rely on the choice of a specific feature appearance descriptor.
Posted Content
Geometric Loss Functions for Camera Pose Regression with Deep Learning
Alex Kendall,Roberto Cipolla +1 more
TL;DR: A number of novel loss functions for learning camera pose which are based on geometry and scene reprojection error are explored, and it is shown how to automatically learn an optimal weighting to simultaneously regress position and orientation.
Proceedings ArticleDOI
Learning to rank in person re-identification with metric ensembles
TL;DR: This work proposes an effective structured learning based approach to the problem of person re-identification which outperforms the current state-of-the-art on most benchmark data sets evaluated and formulates two optimization algorithms, which directly optimize evaluation measures commonly used in person re -identification.
Journal ArticleDOI
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
TL;DR: A fully automatic face recognition algorithm that is multimodal (2D and 3D) and performs hybrid (feature based and holistic) matching in order to achieve efficiency and robustness to facial expressions is presented.
References
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Proceedings ArticleDOI
Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
Book
Multiple view geometry in computer vision
Richard Hartley,Andrew Zisserman +1 more
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Multiple View Geometry in Computer Vision.
TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Journal ArticleDOI
Robust wide-baseline stereo from maximally stable extremal regions
TL;DR: The high utility of MSERs, multiple measurement regions and the robust metric is demonstrated in wide-baseline experiments on image pairs from both indoor and outdoor scenes.