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
Geodesic Matting: A Framework for Fast Interactive Image and Video Segmentation and Matting
Xue Bai,Guillermo Sapiro +1 more
TL;DR: An interactive framework for soft segmentation and matting of natural images and videos is presented in this article, which is based on the optimal, linear time, computation of weighted geodesic distances to user-provided scribbles, from which the whole data is automatically segmented.
Proceedings ArticleDOI
Consumer video understanding: a benchmark database and an evaluation of human and machine performance
TL;DR: A new database, CCV, containing 9,317 web videos over 20 semantic categories, including events like "baseball" and "parade", scenes like "beach", and objects like "cat" is described and released, finding that humans are much better at understanding categories of nonrigid objects such as "cat", while current automatic techniques are relatively close to humans in recognizing categories that have distinctive background scenes or audio patterns.
Proceedings ArticleDOI
Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS
Motilal Agrawal,Kurt Konolige +1 more
TL;DR: A real-time, low-cost system to localize a mobile robot in outdoor environments that relies on stereo vision to robustly estimate frame-to-frame motion in real time and uses inertial measurements to fill in motion estimates when visual odometry fails.
Proceedings ArticleDOI
TILDE: A Temporally Invariant Learned DEtector
TL;DR: In this article, a learning-based approach is proposed to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive.
Proceedings ArticleDOI
Spatial pyramid co-occurrence for image classification
Yi Yang,Shawn Newsam +1 more
TL;DR: A novel image representation termed spatial pyramid co-occurrence which characterizes both the photometric and geometric aspects of an image which achieves state-of-the-art performance on the Graz-01 object class dataset and performs competitively on the 15 Scene dataset.
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.