Moving Object Detection Using Monocular Vision

被引：0

作者：

Wang, Yin-Tien ^{[1
]}

Chen, Kuo-Wei ^{[1
]}

Chiou, Ming-Jang ^{[1
]}

机构：

[1] Tamkang Univ, Dept Mech & Electromech Engn, Taipei, Taiwan

来源：

INTELLIGENT AUTONOMOUS SYSTEMS 12, VOL 1 | 2013年 / 193卷

关键词：

Moving object detection; simultaneous localization and mapping; speeded-up robust features; monocular vision; LOCALIZATION; ALGORITHM; SLAM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an algorithm for moving object detection (MOD) in robot visual simultaneous localization and mapping (SLAM). The algorithm is designed based on the defining epipolar constraint for the corresponding feature points on image plane. An essential matrix obtained using the state estimator is utilized to represent the epipolar constraint. Meanwhile, the method of speeded-up robust feature (SURF) is employed in the algorithm to provide a robust detection for image features as well as a better description of landmarks and of moving objects in visual SLAM system. Experiment is carried out on a hand-held monocular camera to validate the performances of the proposed algorithm. The results show that the integration of MOD and SURF is efficient for robot navigating in dynamic environments.

引用

页码：183 / 192

页数：10

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