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Journal ArticleDOI

Distinctive Image Features from Scale-Invariant Keypoints

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.

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Citations
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Journal ArticleDOI

Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques

TL;DR: An overview of the newly developed automated image-based reconstruction approach and exclusive features which distinct it from other image- based or conventional photogrammetric techniques is presented and the terrestrial laser scanning approach carried out for reconstruction and comparison of as-built scenes is presented.
Posted Content

DSAC - Differentiable RANSAC for Camera Localization

TL;DR: DSAC is applied to the problem of camera localization, where deep learning has so far failed to improve on traditional approaches, and it is demonstrated that by directly minimizing the expected loss of the output camera poses, robustly estimated by RANSAC, it achieves an increase in accuracy.
Journal ArticleDOI

Randomized Clustering Forests for Image Classification

TL;DR: This work introduces Extremely Randomized Clustering Forests-ensembles of randomly created clustering trees-and shows that they provide more accurate results, much faster training and testing, and good resistance to background clutter.
Journal ArticleDOI

Effective and Efficient Global Context Verification for Image Copy Detection

TL;DR: A fast image similarity measurement based on random verification is proposed to efficiently implement copy detection and the proposed method achieves higher accuracy than the state-of-the-art methods, and has comparable efficiency to the baseline method based on the BOW quantization.
Journal ArticleDOI

Latent Palmprint Matching

TL;DR: This work proposes a latent-to-full palmprint matching system that is needed in forensics and uses minutiae as features and a robust algorithm to estimate ridge direction and frequency in palmprints facilitates minutia extraction even in poor quality palmprints.
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

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

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.
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How can distinctive features theory be applied to elision?

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