Contour based multi-object classification technology

Qing Nie; Shou Yi Zhan

doi:10.1007/978-3-540-88513-9_86

Contour based multi-object classification technology

Qing Nie^*, Shou Yi Zhan

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We propose a contour based feature descriptor for object classification. This method uses polygonal approximation algorithm to simplify contours and use adjacent lines to encode object contours. We demonstrate the high performance of the local contour descriptor within a powerful bag of fteatures classification scheme. Through extensive evaluation on PASCAL 2007 Visual Recognition Challenge dataset set, the test results show that this local contour descriptor has many advantages. It is simple and computation efficient. And it is easy to reuse in other frameworks.

Original language	English
Title of host publication	Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings
Publisher	Springer Verlag
Pages	795-803
Number of pages	9
Edition	PART 1
ISBN (Print)	3540885129, 9783540885122
DOIs	https://doi.org/10.1007/978-3-540-88513-9_86
Publication status	Published - 2008
Event	1st International Conference on Intelligent Robotics and Applications, ICIRA 2008 - Wuhan, China Duration: 15 Oct 2008 → 17 Oct 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	5314 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Conference on Intelligent Robotics and Applications, ICIRA 2008
Country/Territory	China
City	Wuhan
Period	15/10/08 → 17/10/08

Keywords

Bag of features
Contour feature
Feature extraction
Object classification
Object recognition

Access to Document

10.1007/978-3-540-88513-9_86

Cite this

Nie, Q., & Zhan, S. Y. (2008). Contour based multi-object classification technology. In Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings (PART 1 ed., pp. 795-803). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5314 LNAI, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-88513-9_86

Nie, Qing ; Zhan, Shou Yi. / Contour based multi-object classification technology. Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings. PART 1. ed. Springer Verlag, 2008. pp. 795-803 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{a945467f3b274e46ae2f6a6122a97291,

title = "Contour based multi-object classification technology",

abstract = "We propose a contour based feature descriptor for object classification. This method uses polygonal approximation algorithm to simplify contours and use adjacent lines to encode object contours. We demonstrate the high performance of the local contour descriptor within a powerful bag of fteatures classification scheme. Through extensive evaluation on PASCAL 2007 Visual Recognition Challenge dataset set, the test results show that this local contour descriptor has many advantages. It is simple and computation efficient. And it is easy to reuse in other frameworks.",

keywords = "Bag of features, Contour feature, Feature extraction, Object classification, Object recognition",

author = "Qing Nie and Zhan, {Shou Yi}",

year = "2008",

doi = "10.1007/978-3-540-88513-9_86",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings",

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Nie, Q & Zhan, SY 2008, Contour based multi-object classification technology. in Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5314 LNAI, Springer Verlag, pp. 795-803, 1st International Conference on Intelligent Robotics and Applications, ICIRA 2008, Wuhan, China, 15/10/08. https://doi.org/10.1007/978-3-540-88513-9_86

Contour based multi-object classification technology. / Nie, Qing; Zhan, Shou Yi.
Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings. PART 1. ed. Springer Verlag, 2008. p. 795-803 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5314 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhan, Shou Yi

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AB - We propose a contour based feature descriptor for object classification. This method uses polygonal approximation algorithm to simplify contours and use adjacent lines to encode object contours. We demonstrate the high performance of the local contour descriptor within a powerful bag of fteatures classification scheme. Through extensive evaluation on PASCAL 2007 Visual Recognition Challenge dataset set, the test results show that this local contour descriptor has many advantages. It is simple and computation efficient. And it is easy to reuse in other frameworks.

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KW - Contour feature

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SN - 9783540885122

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Nie Q, Zhan SY. Contour based multi-object classification technology. In Intelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings. PART 1 ed. Springer Verlag. 2008. p. 795-803. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-88513-9_86

Contour based multi-object classification technology

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