activity
20192025
most citedSeeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar

148 citations · 350 across the 12 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CV2019★ 148 cited

Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar

Nicolas Scheiner, Florian Kraus, Fangyin Wei +8

Conventional sensor systems record information about directly visible objects, whereas occluded scene components are considered lost in the measurement process. Non-line-of-sight (…

cs.LG2019★ 51 cited

A Multi-Stage Clustering Framework for Automotive Radar Data

Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann +1

Radar sensors provide a unique method for executing environmental perception tasks towards autonomous driving. Especially their capability to perform well in adverse weather condit…

eess.SP2019★ 8 cited

Automated Ground Truth Estimation For Automotive Radar Tracking Applications With Portable GNSS And IMU Devices

Nicolas Scheiner, Stefan Haag, Nils Appenrodt +4

Baseline generation for tracking applications is a difficult task when working with real world radar data. Data sparsity usually only allows an indirect way of estimating the origi…

cs.LG2019★ 39 cited

Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles

Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann +1

Radar-based road user classification is an important yet still challenging task towards autonomous driving applications. The resolution of conventional automotive radar sensors res…

cs.LG2019★ 41 cited

Radar-based Feature Design and Multiclass Classification for Road User Recognition

Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann +1

The classification of individual traffic participants is a complex task, especially for challenging scenarios with multiple road users or under bad weather conditions. Radar sensor…

eess.SP2019★ 16 cited

Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS

Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann +1

Annotating automotive radar data is a difficult task. This article presents an automated way of acquiring data labels which uses a highly accurate and portable global navigation sa…