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
More filters
Posted Content
Image-based localization using LSTMs for structured feature correlation
Florian Walch,Caner Hazirbas,Laura Leal-Taixé,Torsten Sattler,Sebastian Hilsenbeck,Daniel Cremers +5 more
TL;DR: In this article, a new CNN+LSTM architecture for camera pose regression for indoor and outdoor scenes is proposed, which makes use of LSTM units on the CNN output, which play the role of a structured dimensionality reduction on the feature vector.
Journal ArticleDOI
Using Inertial Sensors for Position and Orientation Estimation
TL;DR: In recent years, micro-machined electromechanical system inertial sensors (3D accelerometers and 3D gyroscopes) have become widely available due to their small size and low cost.
Proceedings ArticleDOI
Unsupervised 3D object recognition and reconstruction in unordered datasets
Matthew Brown,David G. Lowe +1 more
TL;DR: This paper presents a system for fully automatic recognition and reconstruction of 3D objects in image databases, using invariant local features to find matches between all images, and the RANSAC algorithm to find those that are consistent with the fundamental matrix.
Journal ArticleDOI
Twin Gaussian Processes for Structured Prediction
Liefeng Bo,Cristian Sminchisescu +1 more
TL;DR: Twin Gaussian processes (TGP), a generic structured prediction method that uses Gaussian process priors on both covariates and responses, both multivariate, and estimates outputs by minimizing the Kullback-Leibler divergence between two GP modeled as normal distributions over finite index sets of training and testing examples, is described.
Posted Content
Universal Correspondence Network
TL;DR: A convolutional spatial transformer to mimic patch normalization in traditional features like SIFT is proposed, which is shown to dramatically boost accuracy for semantic correspondences across intra-class shape variations.
References
More filters
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.