A Novel Ant Colony Detection Using Multi-Region Histogram for Object Tracking

Seid Miad Zandavi, Feng Sha, Vera Chung, Zhicheng Lu, Weiming Zhi

Research output: Book chapter/Published conference paperConference paperpeer-review

2 Citations (Scopus)

Abstract

Efficient object tracking become more popular in video processing domain. In recent years, many researchers have developed excellent models and methods for complicated tracking problems in real environment. Among those approaches, object feature definition is one of the most important component to obtain better accuracy in tracking. In this paper, we propose a novel multi-region feature selection method which defines histogram values of basic areas and random areas (MRH) and combined with continuous ant colony filter detection to represent the original target. The proposed approach also achieves smooth tracking on different video sequences, especially with Motion Blur problem. This approach is designed and tested in MATLAB 2016b environment. The experiment result demonstrates better and faster tracking performance and shows continuous tracking trajectory and competitive outcomes regarding to traditional methods.

Original languageEnglish
Title of host publicationNeural Information Processing - 24th International Conference, ICONIP 2017, Proceedings
EditorsDerong Liu, Shengli Xie, El-Sayed M. El-Alfy, Dongbin Zhao, Yuanqing Li
PublisherSpringer-Verlag Italia Srl
Pages25-33
Number of pages9
ISBN (Print)9783319700892
DOIs
Publication statusPublished - 2017
Event24th International Conference on Neural Information Processing, ICONIP 2017 - Guangzhou, China
Duration: 14 Nov 201718 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10636 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Neural Information Processing, ICONIP 2017
Country/TerritoryChina
CityGuangzhou
Period14/11/1718/11/17

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