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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Proceedings ArticleDOI
Evaluation of features detectors and descriptors based on 3D objects
Pierre Moreels,Pietro Perona +1 more
TL;DR: A method is designed, based on intersecting epipolar constraints, for providing ground truth correspondence automatically and it is found that the combination of Hessian-affine feature finder and SIFT features is most robust to viewpoint change.
Proceedings ArticleDOI
Learning invariant features through topographic filter maps
TL;DR: This work proposes a method that automatically learns feature extractors in an unsupervised fashion by simultaneously learning the filters and the pooling units that combine multiple filter outputs together.
Proceedings ArticleDOI
Beyond the Euclidean distance: Creating effective visual codebooks using the Histogram Intersection Kernel
Jianxin Wu,James M. Rehg +1 more
TL;DR: It is demonstrated that HIK can also be used in an unsupervised manner to significantly improve the generation of visual codebooks and the standard k-median clustering method can be used for visual codebook generation and can act as a compromise between HIK and k-means approaches.
Book ChapterDOI
Co-occurrence Histograms of Oriented Gradients for Pedestrian Detection
TL;DR: This paper proposes a method for extracting feature descriptors consisting of co-occurrence histograms of oriented gradients (CoHOG) that reduces miss rate by half compared with HOG, and outperforms the state-of-the-art methods on both datasets.
Proceedings ArticleDOI
Geometric min-Hashing: Finding a (thick) needle in a haystack
TL;DR: The proposed geometric min-hashing approach is a novel hashing scheme for image retrieval, clustering and automatic object discovery that has both higher recall and lower false positive rates than the state-of-the-art min-hash.
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.