Reliable People Detection Using Range and Intensity Data from Multiple Layers of Laser Range Finders on a Mobile Robot
Reliable People Detection Using Range and Intensity Data from Multiple Layers of Laser Range Finders on a Mobile Robot
复制标题
使用移动机器人上多层激光测距仪的距离和强度数据进行可靠的人员检测
DOI：
10.1007/s12369-010-0086-3
复制
发表时间：
2011
影响因子：
4.7
通讯作者：
S. Yuta
中科院分区：
文献类型：
--
作者：
Alexander Carballo;A. Ohya;S. Yuta
可靠的人员检测是安全、智能环境和人机交互等多个领域的一项重要任务。人员检测不仅仅取决于静态环境对象与运动对象（希望是人类）的分离，即使在杂乱的环境中，可靠的系统也应该能够检测静态人员。这项工作提出了一种在移动机器人上使用多层激光测距仪（LRF）进行人员检测和位置估计的可靠方法。每层都结合了两个 LRF 传感器来扫描机器人周围的环境，并垂直分开以检测人体的不同部位。通过使用 AdaBoost，我们创建了强大的分类器来检测身体部位，融合每一层中的候选片段以进行人员检测，并且我们使用简单的数据关联来估计它们的位置。此外，这项工作引入了激光反射强度作为人员检测的新特性。首先，我们提出了激光强度和纺织品的研究，然后引入了新的基于强度的检测特征，并提出了一种使用激光强度进行片段分离的方法。我们通过在移动机器人上进行的多次实验对我们的多层系统进行了全面的评估。
Reliable people detection is an important task in several areas like security, intelligent environments and human robot interaction. People detection does not depend only upon separation of static environment objects from those showing motion (hopefully humans), a reliable system should be able to detect static people even in cluttered environments.This work presents a reliable approach for people detection and position estimation using multiple layers of Laser Range Finders (LRF) on a mobile robot. Each layer combines two LRF sensors to scan around the robot’s surroundings and are vertically separated to detect distinct parts of the human body. By using AdaBoost we create strong classifiers to detect body parts, candidate segments in each layer are fused for people detection, and we use simple data association to estimate their positions. Additionally, this work introduces laser reflection intensity as a novel property for people detection. First, we present a study of laser intensity and textiles, then introduce new intensity-based features for detection, and propose a method for segment separation using laser intensity. We provide a thorough evaluation of our multi-layered system though several experiments on a mobile robot.
使用移动平台上的单行激光测距扫描仪监控人口稠密的环境
DOI：
--
发表时间：
2007
期刊：
IEEE Int.Conf.on Robotics and Automation(ICRA)
影响因子：
--
作者：
Zhao;H.;Chen;Y.;Shao;X.W.;Katabira;K.;Shibasaki;R.
通讯作者：
R.