Real-time Object Segmentation for Soccer Robots Based on Depth Images

被引：0

作者：

Cheng, Qiu ^{[1
]}

Yu, Shuijun ^{[1
]}

Yu, Qinghua ^{[1
]}

Xiao, Junhao ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Mechatron & Automat, Changsha, Hunan, Peoples R China

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA) | 2016年

基金：

美国国家科学基金会;

关键词：

RoboCup; object detection; point cloud segmentation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Object detection and localization is a paramount important and challenging task in RoboCup MSL (Middle Size League). It has a strong constraint on real-time, as both the robot and obstacles (also robots) are moving quickly. In this paper, a real-time object segmentation approach is proposed, based on a RGB-D camera in which only the range information has been used. The method has four main steps, e.g., point cloud filtering, background points removing, clustering and object localization. Experimental results show that the proposed algorithm can effectively detect and segment objects in 3D space in real-time.

引用

页码：1532 / 1537

页数：6

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