RadarScenes: A Real-World Radar Point Cloud Data Set for Automotive Applications

被引：0

作者：

Schumann, Ole ^{[1
]}

Hahn, Markus ^{[2
]}

Scheiner, Nicolas ^{[1
]}

Weishaupt, Fabio ^{[1
]}

Tilly, Julius F. ^{[1
]}

Dickmann, Jurgen ^{[1
]}

Woehler, Christian ^{[3
]}

机构：

[1] Mercedes Benz AG, Environm Percept, Stuttgart, Germany

[2] Daimler AG, Continental AG, Ulm, Germany

[3] TU Dortmund, Fac Elect Engn & Informat Technol, Dortmund, Germany

来源：

2021 IEEE 24TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) | 2021年

关键词：

dataset; radar; machine learning; classification;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

A new automotive radar data set with measurements and point-wise annotations from more than four hours of driving is presented. Data provided by four series radar sensors mounted on one test vehicle were recorded and the individual detections of dynamic objects were manually grouped to clusters and labeled afterwards. The purpose of this data set is to enable the development of novel (machine learning-based) radar perception algorithms with the focus on moving road users. Images of the recorded sequences were captured using a documentary camera. For the evaluation of future object detection and classification algorithms, proposals for score calculation are made so that researchers can evaluate their algorithms on a common basis. Additional information as well as download instructions can be found on the website of the data set: www.radar-scenes.com.

引用

页码：939 / 946

页数：8

共 28 条

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