The DEBS 2019 grand challenge
Paper in proceedings, 2019

The ACM DEBS 2019 Grand Challenge is the ninth in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2019 Grand Challenge is on the application of machine learning to LiDAR data. The goal of the challenge is to perform classification of objects found in urban environments and sensed in several 3D scenes by the LiDAR. The applications of LIDAR and object detection go well beyond autonomous vehicles and are suitable for use in agriculture, waterway maintenance and flood prevention, and construction. This paper describes the specifics of the data streams provided in the challenge as well as the benchmarking platform that supports the testing of corresponding solutions.

LiDAR

Event processing

Point cloud

Streaming

Author

Oleh Bodunov

Technische Universität Dresden

Vincenzo Massimiliano Gulisano

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Hannaneh Najdataei

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Zbigniew Jerzak

Zalando SE

André Martin

Technische Universität Dresden

Pavel Smirnov

AGT International GmbH

M. Strohbach

AGT International GmbH

Holger Ziekow

Hochschule Furtwangen (HFU)

DEBS 2019 - Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems

205-208

13th ACM International Conference on Distributed and Event-Based Systems
Darmstadt, Germany,

Subject Categories

Robotics

Computer Science

Computer Systems

DOI

10.1145/3328905.3334135

More information

Latest update

12/5/2019