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Maximally stable extremal regions
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1	Robust Wide Baseline Stereo from Maximally Stable Extremal Regions J. Matas1,2 , O. Chum1 , M. Urban1 , T. Pajdla1 1 Center for Machine Perception, Dept. of Cybernetics, CTU Prague, Karlovo n´am 13, CZ Add to Reading List Source URL: cmp.felk.cvut.cz Language: English - Date: 2002-09-12 09:47:17
2	Copyright 2013 IEEE. Published in the IEEE 2013 International Conference on Image Processing (ICIP 2013), scheduled for September, 2013 in Melbourne, Australia. Personal use of this material is permitted. However Add to Reading List Source URL: w3.ualg.pt Language: English - Date: 2013-06-18 13:19:51 Feature detection IEEE conferences Image processing California Institute of Technology Caltech 101 Conference on Computer Vision and Pattern Recognition Outline of object recognition Speeded up robust features International Conference on Computer Vision Gabor filter Maximally stable extremal regions Scale-invariant feature transform
3	Position Interpolation using Feature Point Scale for Decimeter Visual Localization David Wong, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase Graduate School of Information Science, Nagoya University Furo-cho, Chikusa-ku, N Add to Reading List Source URL: www.murase.m.is.nagoya-u.ac.jp Language: English - Date: 2016-03-22 02:21:57 Feature detection Scale-invariant feature transform Speeded up robust features Feature Image registration Corner detection Simultaneous localization and mapping Triangulation Maximally stable extremal regions Outline of object recognition Bag-of-words model in computer vision
4	Detecting Mars Surface Change Using Landmark Comparison Julian Panetta Mentor: Kiri Wagstaff October 28, 2009 Add to Reading List Source URL: julianpanetta.com Language: English - Date: 2012-01-24 03:47:32 Computer vision Combinatorial optimization Matching RANSAC Bipartite graph Image registration Graph Maximally stable extremal regions
5	Local Convolutional Features with Unsupervised Training for Image Retrieval Mattis Paulin 1 Julien Mairal1 1 Inria ∗ Add to Reading List Source URL: www.cv-foundation.org Language: English - Date: 2015-10-24 14:55:25 Feature detection Computer vision Artificial intelligence Vision Computational neuroscience Convolutional neural network Deep learning Outline of object recognition Maximally stable extremal regions Visual descriptor GLOH Conference on Computer Vision and Pattern Recognition
6	D:/workspace/FIONA/Doc/Reviews/ICPRAM_2012/SenstUngerTU.dvi Add to Reading List Source URL: elvera.nue.tu-berlin.de Language: English - Date: 2012-03-14 04:57:00 Imaging Optics Maximally stable extremal regions SURF Corner detection Kanade–Lucas–Tomasi feature tracker Feature detection Object recognition Optical flow Computer vision Image processing Vision
7	Global Context Descriptors for SURF and MSER Feature Descriptors Gail Carmichael School of Computer Science Carleton University Ottawa, ON, Canada, K1S 5B6 Add to Reading List Source URL: www.site.uottawa.ca Language: English - Date: 2012-05-22 14:45:00 Artificial intelligence Maximally stable extremal regions Feature detection Object recognition SURF Feature Corner detection Geometric hashing Image gradient Computer vision Image processing Vision
8	Robotic Manipulation Strategies for Detecting and Reading Text Alan Broun, Chris Beck, Tony Pipe, Majid Mirmehdi, Chris Melhuish I. INTRODUCTION Text is everywhere in the modern world, and provides a valuable store of in Add to Reading List Source URL: www.alanbroun.net Language: English Maximally stable extremal regions Robot Pose Document Object Model Artificial intelligence Computer programming Computer vision Computing Robotics
9	Edge Foci Interest Points C. Lawrence Zitnick Microsoft Research Redmond, WA Krishnan Ramnath Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2011-08-05 18:36:58 Vision Optics Hessian affine region detector Harris affine region detector Feature detection Maximally stable extremal regions Scale space Interest point detection Edge detection Computer vision Image processing Imaging
10	Image Matching using Local Symmetry Features Daniel Cabrini Hauagge Noah Snavely Cornell University {hauagge,snavely}@cs.cornell.edu Add to Reading List Source URL: www.cs.cornell.edu Language: English - Date: 2012-06-03 17:02:52 Geometry Optics Feature detection Maximally stable extremal regions Object recognition Reflection symmetry Shape context Rotational symmetry Local symmetry Computer vision Symmetry Vision