Article

Efficient Maximally Stable Extremal Region (MSER) Tracking

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CVPR '06: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1

Pages 553 - 560

https://doi.org/10.1109/CVPR.2006.107

Published: 17 June 2006 Publication History

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Abstract

This paper introduces a tracking method for the well known local MSER (Maximally Stable Extremal Region) detector. The component tree is used as an efficient data structure, which allows the calculation of MSERs in quasi-linear time. It is demonstrated that the tree is able to manage the required data for tracking. We show that by means of MSER tracking the computational time for the detection of single MSERs can be improved by a factor of 4 to 10. Using a weighted feature vector for data association improves the tracking stability. Furthermore, the component tree enables backward tracking which further improves the robustness. The novel MSER tracking algorithm is evaluated on a variety of scenes. In addition, we demonstrate three different applications, tracking of license plates, faces and fibers in paper, showing in all three scenarios improved speed and stability.

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Lui CMaged AXie M(2024)A novel image feature based self-supervised learning model for effective quality inspection in additive manufacturingJournal of Intelligent Manufacturing10.1007/s10845-023-02232-y35:7(3543-3558)Online publication date: 1-Oct-2024
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Efficient Maximally Stable Extremal Region (MSER) Tracking

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CVPR '06: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1

June 2006

12293 pages

ISBN:0769525970

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IEEE Computer Society

United States

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Published: 17 June 2006

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Mohanta SVeer K(2024)Soft Computing Based Comparative Model for the Classification of Facial Expression RecognitionWireless Personal Communications: An International Journal10.1007/s11277-024-11414-7136:4(2573-2594)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s11277-024-11414-7
Lui CMaged AXie M(2024)A novel image feature based self-supervised learning model for effective quality inspection in additive manufacturingJournal of Intelligent Manufacturing10.1007/s10845-023-02232-y35:7(3543-3558)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1007/s10845-023-02232-y
Wu HXie HLin FZhang SSun JZhang Y(2019)WaveCSNProceedings of the 1st ACM International Conference on Multimedia in Asia10.1145/3338533.3366574(1-6)Online publication date: 15-Dec-2019
https://dl.acm.org/doi/10.1145/3338533.3366574
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Soni RKumar BChand S(2019)Text detection and localization in natural scene images based on text awareness scoreApplied Intelligence10.1007/s10489-018-1338-449:4(1376-1405)Online publication date: 1-Apr-2019
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Song YChen JXie HChen ZGao XChen X(2017)Robust and parallel Uyghur text localization in complex background imagesMachine Vision and Applications10.1007/s00138-017-0837-328:7(755-769)Online publication date: 1-Oct-2017
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Zhu HSheng JZhang FZhou JWang J(2016)Improved maximally stable extremal regions based method for the segmentation of ultrasonic liver imagesMultimedia Tools and Applications10.1007/s11042-015-2822-z75:18(10979-10997)Online publication date: 1-Sep-2016
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Nagai YKamisaka DMakibuchi NXu JSakazawa SZhou XSmeaton ATian QBulterman DShen HMayer-Patel KYan S(2015)3D Person Tracking In World Coordinates and Attribute Estimation with PDRProceedings of the 23rd ACM international conference on Multimedia10.1145/2733373.2806301(1139-1142)Online publication date: 13-Oct-2015
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Shape Guided Maximally Stable Extremal Region (MSER) Tracking

Maximally Stable Texture Regions

Video stabilization using maximally stable extremal region features

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