Self-monitoring to improve robustness of 3D object tracking for robotics

2011 ◽  
Author(s):  
Thomas Morwald ◽  
Michael Zillich ◽  
Johann Prankl ◽  
Markus Vincze
Keyword(s):  
Object Tracking ◽  
Self Monitoring ◽  
3D Object

scholarly journals A Two-Stage Data Association Approach for 3D Multi-Object Tracking

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2894
Author(s):  
Minh-Quan Dao ◽  
Vincent Frémont
Keyword(s):  
Object Detection ◽  
Object Tracking ◽  
Moving Objects ◽  
Data Association ◽  
Autonomous Driving ◽  
Tracking Accuracy ◽  
Two Stage ◽  
Bipartite Matching ◽  
3D Object ◽  
3D Object Detection

Multi-Object Tracking (MOT) is an integral part of any autonomous driving pipelines because it produces trajectories of other moving objects in the scene and predicts their future motion. Thanks to the recent advances in 3D object detection enabled by deep learning, track-by-detection has become the dominant paradigm in 3D MOT. In this paradigm, a MOT system is essentially made of an object detector and a data association algorithm which establishes track-to-detection correspondence. While 3D object detection has been actively researched, association algorithms for 3D MOT has settled at bipartite matching formulated as a Linear Assignment Problem (LAP) and solved by the Hungarian algorithm. In this paper, we adapt a two-stage data association method which was successfully applied to image-based tracking to the 3D setting, thus providing an alternative for data association for 3D MOT. Our method outperforms the baseline using one-stage bipartite matching for data association by achieving 0.587 Average Multi-Object Tracking Accuracy (AMOTA) in NuScenes validation set and 0.365 AMOTA (at level 2) in Waymo test set.

Correlation-based particle filter for 3D object tracking

2009 ◽  
Vol 16 (2) ◽  
pp. 165-177 ◽  
Author(s):  
Jean-Charles Noyer ◽  
Patrick Lanvin ◽  
Mohammed Benjelloun
Keyword(s):  
Particle Filter ◽  
Object Tracking ◽  
3D Object

Robust 3D Object Tracking from Monocular Images Using Stable Parts

2018 ◽  
Vol 40 (6) ◽  
pp. 1465-1479 ◽  
Author(s):  
Alberto Crivellaro ◽  
Mahdi Rad ◽  
Yannick Verdie ◽  
Kwang Moo Yi ◽  
Pascal Fua ◽  
...  
Keyword(s):  
Object Tracking ◽  
3D Object

Manipulator and object tracking for in-hand 3D object modeling

2011 ◽  
Vol 30 (11) ◽  
pp. 1311-1327 ◽  
Author(s):  
Michael Krainin ◽  
Peter Henry ◽  
Xiaofeng Ren ◽  
Dieter Fox
Keyword(s):  
Object Tracking ◽  
Object Modeling ◽  
3D Object ◽  
3D Object Modeling
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