Cooperative moving-object tracking with multiple mobile sensor nodes — Size and posture estimation of moving objects using in-vehicle multilayer laser scanner

2016 ◽  
Author(s):  
Shota Kanaki ◽  
Koki Fujishita ◽  
Masafumi Hashimoto ◽  
Ryohei Murabayashi ◽  
Kimiaki Inui ◽  
...  
Keyword(s):  
Object Tracking ◽  
Moving Objects ◽  
Laser Scanner ◽  
Moving Object ◽  
Sensor Nodes ◽  
Mobile Sensor ◽  
Posture Estimation ◽  
Mobile Sensor Nodes ◽  
Moving Object Tracking

Moving-object Tracking Using Only Data from Onboard Laser Scanner

2018 ◽  
Vol 2018 (0) ◽  
pp. 1P2-A09 ◽  
Author(s):  
Yohei MATSUI ◽  
Misato YAMAJI ◽  
Masafumi HASHIMOTO ◽  
Kazuhiko TAKAHASHI
Keyword(s):  
Object Tracking ◽  
Laser Scanner ◽  
Moving Object ◽  
Moving Object Tracking

scholarly journals Moving-Object Tracking with In-Vehicle Multi-Laser Range Sensors

2008 ◽  
Vol 20 (3) ◽  
pp. 367-377 ◽  
Author(s):  
Masafumi Hashimoto ◽  
◽  
Yosuke Matsui ◽  
Kazuhiko Takahashi ◽  
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Moving Objects ◽  
Tracking System ◽  
Moving Object ◽  
Experimental Result ◽  
Coordinate Frame ◽  
Laser Range ◽  
Assignment Algorithm ◽  
Moving Object Tracking

This paper presents a method for moving-object tracking with in-vehicle 2D laser range sensor (LRS) in a cluttered environment. A sensing area of one LRS is limited in orientation, and hence the mobile robot is equipped with multi-LRSs for omnidirectional sensing. Since each LRS takes the laser image on its own local coordinate frame, the laser image is mapped onto a reference coordinate frame so that the object tracking can be achieved by cooperation of multi-LRSs. For mapping the coordinate frames of multi-LRSs are calibrated, that is, the relative positions and orientations of the multi-LRSs are estimated. The calibration is based on Kalman filter and chi-hypothesis testing. Moving-object tracking is achieved by two steps: detection and tracking. Each LRS finds moving objects from its own laser image via a heuristic rule and an occupancy grid based method. It tracks the moving objects via Kalman filter and the assignment algorithm based data association. When the moving objects exist in the overlapped sensing areas of the LRSs, these LRSs exchange the tracking data and fuse them in a decentralized manner. A rule based track management is embedded into the tracking system in order to enhance the tracking performance. The experimental result of three walking-people tracking in an indoor environment validates the proposed method.

scholarly journals Moving-object tracking using laser scanner mounted on two-wheeled vehicle based on environmental map subtraction

2019 ◽  
Vol 85 (878) ◽  
pp. 19-00056-19-00056
Author(s):  
Yohei MATSUI ◽  
Shotaro MURO ◽  
Masafumi HASHIMOTO ◽  
Kazuhiko TAKAHASHI
Keyword(s):  
Object Tracking ◽  
Laser Scanner ◽  
Moving Object ◽  
Wheeled Vehicle ◽  
Moving Object Tracking ◽  
Environmental Map

Rotation adaptive correlation filter for moving object tracking in satellite videos

2021 ◽  
Vol 438 ◽  
pp. 94-106
Author(s):  
Shiyu Xuan ◽  
Shengyang Li ◽  
Zifei Zhao ◽  
Zhuang Zhou ◽  
Wanfeng Zhang ◽  
...  
Keyword(s):  
Object Tracking ◽  
Moving Object ◽  
Correlation Filter ◽  
Moving Object Tracking
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