Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 232,057,476 papers from all fields of science
Search
Sign In
Create Free Account
Maximally stable extremal regions
Known as:
MSER
In computer vision, maximally stable extremal regions (MSER) are used as a method of blob detection in images. This technique was proposed by Matas…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
10 relations
Blob detection
Computer vision
Correspondence problem
Eight-point algorithm
Expand
Broader (1)
Feature detection (computer vision)
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Symbolic road marking recognition using convolutional neural networks
Touqeer Ahmad
,
David Ilstrup
,
Ebrahim Emami
,
G. Bebis
IEEE Intelligent Vehicles Symposium (IV)
2017
Corpus ID: 12139428
This paper investigates the use of Convolutional Neural Networks for classification of painted symbolic road markings. Previous…
Expand
2015
2015
Improved maximally stable extremal regions based method for the segmentation of ultrasonic liver images
Haijiang Zhu
,
Junhui Sheng
,
Fan Zhang
,
Jinglin Zhou
,
Jing Wang
Multimedia tools and applications
2015
Corpus ID: 254834419
The goal of this paper is to propose a modified maximally stable extremal region (MSER) based method for the segmentation of…
Expand
2012
2012
Do humans fixate on interest points?
Akshat Dave
,
Rachit Dubey
,
Bernard Ghanem
International Conference on Pattern Recognition
2012
Corpus ID: 11768944
Interest point detectors (e.g. SIFT, SURF, and MSER) have been successfully applied to numerous applications in high level…
Expand
2011
2011
Maximally Stable Extremal Regions and Local Geometry for Visual Correspondences
České Vysoké
,
Učení Technické
,
V. Praze
,
T. K. D. Práci
,
Michal Perd’och
2011
Corpus ID: 262848041
Teze disertace k získání akademického titulu " doktor " , ve zkratce " Ph.D. " Praha, srpen 2011 Disertační práce byla vypracov…
Expand
2011
2011
Clouds and Shadows Detection in Multi-spectral Satellite Image Based on Maximally Stable Extremal Regions
Yu Tong
,
Wang Ming-shu
International Conference on Multimedia and Signal…
2011
Corpus ID: 6769838
Maximally Stable Extremal Region (MSER) hasbeen proven to be an excellent feature extraction method incomputer vision. The…
Expand
2010
2010
Multi-scale maximally stable extremal regions for object recognition
Ronghua Luo
,
Huaqing Min
The IEEE International Conference on Information…
2010
Corpus ID: 17632383
To solve the problem that maximally stable extremal regions (MSER) will become unstable when the image is blurred due to the…
Expand
2010
2010
Pedestrian detection based on maximally stable extremal regions
Vadim Frolov
,
F. P. León
IEEE Intelligent Vehicles Symposium
2010
Corpus ID: 15317162
This paper presents a new approach to generate hypotheses about the presence of pedestrians in an infrared image. Information…
Expand
2008
2008
Determination of maximally stable extremal regions in large images
Jan Wassenberg
,
D. Bulatov
,
W. Middelmann
,
P. Sanders
2008
Corpus ID: 64128002
Coping with ever-increasing data requires efficient algorithms. The topic of this work is segmentation; we present a new means of…
Expand
2007
2007
An Implementation of Multi-Dimensional Maximally Stable Extremal Regions
A. Vedaldi
2007
Corpus ID: 13061842
We describe an implementation of the Maximally Stable Extremal Region ([3], Sect. 2, MSER) feature detector and an immediate…
Expand
2004
2004
Evaluation of local detectors on non-planar scenes
F. Fraundorfer
,
H. Bischof
2004
Corpus ID: 2140568
This paper presents for the first time a method to evaluate the performance of local detectors under viewpoint changes on complex…
Expand
By clicking accept or continuing to use the site, you agree to the terms outlined in our
Privacy Policy
(opens in a new tab)
,
Terms of Service
(opens in a new tab)
, and
Dataset License
(opens in a new tab)
ACCEPT & CONTINUE