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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Journal ArticleDOI
Robust Point Matching via Vector Field Consensus
TL;DR: This paper proposes an efficient algorithm, called vector field consensus, for establishing robust point correspondences between two sets of points, and suggests a two-stage strategy, where the nonparametric model is used to reduce the size of the putative set and a parametric variant of the approach to estimate the geometric parameters.
Book ChapterDOI
Coloring local feature extraction
TL;DR: The results show that color descriptors remain reliable under photometric and geometrical changes, and with decreasing image quality, and for all experiments a combination of color and shape outperforms a pure shape-based approach.
Proceedings ArticleDOI
Fisher Vector Faces in the Wild.
TL;DR: This paper shows that Fisher vectors on densely sampled SIFT features are capable of achieving state-of-the-art face verification performance on the challenging “Labeled Faces in the Wild” benchmark, and shows that a compact descriptor can be learnt from them using discriminative metric learning.
Proceedings ArticleDOI
Automatic camera and range sensor calibration using a single shot
TL;DR: It is demonstrated that the proposed checkerboard corner detector significantly outperforms current state-of-the-art and the proposed camera-to-range registration method is able to discover multiple solutions in the case of ambiguities.
Proceedings ArticleDOI
Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination
Laurent Sifre,Stéphane Mallat +1 more
TL;DR: An affine invariant representation is constructed with a cascade of invariants, which preserves information for classification and state-of-the-art classification results are obtained over texture databases with uncontrolled viewing conditions.
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.