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
Robust Facial Expression Recognition Based on Local Directional Pattern
TL;DR: A new appearance‐based feature descriptor, the local directional pattern (LDP), is presented to represent facial geometry and analyze its performance in expression recognition, showing the superiority of LDP descriptor against other appearance-based feature descriptors.
Proceedings ArticleDOI
Object cosegmentation
TL;DR: This paper adds two new aspects to cosegmentation: “something” has to be an object, and the “similarity” measure is learned, and is able to achieve excellent results on the recently introduced iCoseg dataset.
Journal ArticleDOI
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery
TL;DR: In this article, the authors used combined photogrammetry and Structure from Motion (SfM) approaches to model the forest canopy surface from low-altitude aerial images. And they used the open source and free photogrammetric toolbox, MICMAC (acronym for multi image matches for Auto Correlation Methods), to create a digital canopy surface model of deciduous stands.
Book ChapterDOI
VolumeDeform: Real-Time Volumetric Non-rigid Reconstruction
TL;DR: In this paper, a single hand-held consumer-grade RGB-D sensor at real-time rates is used to reconstruct dynamic geometric shapes using a set of sparse color features in combination with a dense depth constraint.
Posted Content
LIFT: Learned Invariant Feature Transform
TL;DR: In this article, a novel deep network architecture is introduced that implements the full feature point handling pipeline, that is, detection, orientation estimation, and feature description, in a unified manner while preserving end-to-end differentiability.
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.