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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Book
State Estimation for Robotics
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Proceedings ArticleDOI
Near Duplicate Image Detection: min-Hash and tf-idf Weighting.
TL;DR: This paper proposes two novel image similarity measures for fast indexing via locality sensitive hashing and an efficient way of exploiting more sophisticated similarity measures that have proven to be essential in image / particular object retrieval.
Journal ArticleDOI
Efficient Visual Search of Videos Cast as Text Retrieval
Josef Sivic,Andrew Zisserman +1 more
TL;DR: An approach to object retrieval which searches for and localizes all the occurrences of an object in a video, given a query image of the object, and investigates retrieval performance with respect to different quantizations of region descriptors and compares the performance of several ranking measures.
Journal ArticleDOI
RTAB-Map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation
Mathieu Labbé,François Michaud +1 more
TL;DR: This paper presents this extended version of RTAB‐Map and its use in comparing, both quantitatively and qualitatively, a large selection of popular real‐world datasets, outlining strengths, and limitations of visual and lidar SLAM configurations from a practical perspective for autonomous navigation applications.
Journal ArticleDOI
Visual-inertial navigation, mapping and localization: A scalable real-time causal approach
Eagle Jones,Stefano Soatto +1 more
TL;DR: An integrated approach to ‘loop-closure’, that is the recognition of previously seen locations and the topological re-adjustment of the traveled path, is described, where loop-closure can be performed without the need to re-compute past trajectories or perform bundle adjustment.
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.