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.read more
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
Eric Brachmann,Alexander Krull,Sebastian Nowozin,Jamie Shotton,Frank Michel,Stefan Gumhold,Carsten Rother +6 more
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
Anil K. Jain,Jianjiang Feng +1 more
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
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.