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
DeepMatching: Hierarchical Deformable Dense Matching
TL;DR: A novel matching algorithm, called DeepMatching, to compute dense correspondences between images, which outperforms the state-of-the-art algorithms and shows excellent results in particular for repetitive textures.
Proceedings ArticleDOI
Project-Out Cascaded Regression with an application to face alignment
TL;DR: Based on the principles of PO-CR, a face alignment system that produces remarkably accurate results on the challenging iBUG data set outperforming previously proposed systems by a large margin.
Journal ArticleDOI
Consistency Analysis and Improvement of Vision-aided Inertial Navigation
TL;DR: An observability constrained VINS (OC-VINS), which explicitly enforces the unobservable directions of the system, hence preventing spurious information gain and reducing inconsistency is developed.
Journal ArticleDOI
Recent progress in semantic image segmentation
TL;DR: In this paper, the authors divide semantic image segmentation methods into two categories: traditional and recent DNN method, and comprehensively investigate recent methods based on DNN which are described in the eight aspects: fully convolutional network, upsample ways, FCN joint with CRF methods, dilated convolution approaches, progresses in backbone network, pyramid methods, multi-level feature and multi-stage method, supervised, weakly-supervised and unsupervised methods.
Proceedings ArticleDOI
Region Classification with Markov Field Aspect Models
Jakob Verbeek,Bill Triggs +1 more
TL;DR: Combining spatial and aspect models significantly improves the region-level classification accuracy, and models trained with image-level labels outperform PLSA trained with pixel-level ones.
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.