|
Descripción
|
|
|---|---|
| Urban-oriented autonomous vehicles require a reliable perception technology to tackle the high amount of uncertainties. The recently introduced compact 3D LIDAR sensor offers a surround spatial information that can be exploited to enhance the vehicle perception. We present a real-time integrated framework of multitarget object detection and tracking using 3D LIDAR geared toward urban use. Our approach combines sensor occlusion-aware detection method with computationally efficient heuristics rule-based filtering and adaptive probabilistic tracking to handle uncertainties arising from sensing limitation of 3D LIDAR and complexity of the target object movement. The evaluation results using real-world pre-recorded 3D LIDAR data and comparison with state-of-the-art works shows that our framework is capable of achieving promising tracking performance in the urban situation | |
|
Internacional
|
Si |
|
Nombre congreso
|
The purpose of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) |
|
Tipo de participación
|
960 |
|
Lugar del congreso
|
|
|
Revisores
|
Si |
|
ISBN o ISSN
|
978-989-758-293-6 |
|
DOI
|
|
|
Fecha inicio congreso
|
16/03/2018 |
|
Fecha fin congreso
|
18/03/2018 |
|
Desde la página
|
0 |
|
Hasta la página
|
0 |
|
Título de las actas
|
Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties |