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
Editor's Choice Article: A survey of approaches and trends in person re-identification
TL;DR: The problem of person re-identification is explored and open issues and challenges of the problem are highlighted with a discussion on potential directions for further research.
Proceedings ArticleDOI
Large-scale image classification: Fast feature extraction and SVM training
Yuanqing Lin,Fengjun Lv,Shenghuo Zhu,Ming Yang,Timothee Cour,Kai Yu,Liangliang Cao,Thomas S. Huang +7 more
TL;DR: A parallel averaging stochastic gradient descent (ASGD) algorithm for training one-against-all 1000-class SVM classifiers and a Hadoop scheme that performs feature extraction in parallel using hundreds of mappers, which achieves state-of-the-art performance on the ImageNet 1000- class classification.
Patent
Method and apparatus for estimating body shape
Michael J. Black,Alexandru O. Balan,Alexander Weiss,Leonid Sigal,Matthew Loper,Timothy S. St. Clair +5 more
TL;DR: In this paper, a system and method of estimating the body shape of an individual from input data such as images or range maps is presented. But the body may appear in one or more poses captured at different times and a consistent body shape is computed for all poses.
Proceedings ArticleDOI
Multi-spectral SIFT for scene category recognition
Matthew Brown,Sabine Süsstrunk +1 more
TL;DR: It is shown that the addition of near-infrared information leads to significantly improved performance in a scene-recognition task, and that the improvements are greater still when an appropriate 4-dimensional colour representation is used.
Proceedings ArticleDOI
Image Based Localization in Urban Environments
Wei Zhang,Jana Kosecka +1 more
TL;DR: A prototype system for image based localization in urban environments given a database of views of city street scenes tagged by GPS locations, the system computes the GPS location of a novel query view by using a wide-baseline matching technique based on SIFT features.
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.