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Document type:
Konferenzbeitrag 
Author(s):
Steyer, S.; Tanzmeister, G.; Lenk, C.; Dallabetta, V.; Wollherr, D. 
Title:
Data Association for Grid-Based Object Tracking Using Particle Labeling 
Abstract:
Estimating surrounding objects and obstacles by processing sensor data is essential for safe autonomous driving. Grid-based approaches discretize the environment into grid cells, which implicitly solves the data association between measurement data and the filtered state on this grid representation. Recent approaches estimate, in addition to occupancy probabilities, cell velocity distributions using a low-level particle filter. Measured occupancy can thus be classified as static or dynamic, wher...    »
 
Keywords:
object detection; object tracking; particle filtering (numerical methods); target tracking; traffic engineering computing; data association; grid-based object tracking; particle labeling; surrounding objects; sensor data; safe autonomous driving; grid cells; measurement data; filtered state; grid representation; cell velocity distributions; measured occupancy; subsequent tracking; moving objects; dynamic cells; multiple predicted objects; high-level objects; object label; particle label distribu...    »
 
Book / Congress title:
2018 21st International Conference on Intelligent Transportation Systems (ITSC) 
Organization:
IEEE 
Date of congress:
November 4-7, 2018 
Year:
2018 
Month:
Nov 
Pages:
3036-3043 
Semester:
WS 18-19