PEDESTRIAN DETECTION AND TRACKING IN SPARSE MLS POINT CLOUDS USING A NEURAL NETWORK AND VOTING-BASED APPROACH
This paper presents and extends an approach for the detection of pedestrians in unstructured point clouds resulting from single MLS (mobile laser scanning) scans. The approach is based on a neural network and a subsequent voting process. The neural network processes point clouds subdivided into loca...
Main Authors: | B. Borgmann, M. Hebel, M. Arens, U. Stilla |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2020-08-01
|
Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2020/187/2020/isprs-annals-V-2-2020-187-2020.pdf |
Similar Items
-
DETECTION OF PERSONS IN MLS POINT CLOUDS
by: B. Borgmann, et al.
Published: (2017-09-01) -
USING NEURAL NETWORKS TO DETECT OBJECTS IN MLS POINT CLOUDS BASED ON LOCAL POINT NEIGHBORHOODS
by: B. Borgmann, et al.
Published: (2019-09-01) -
INFORMATION ACQUISITION ON PEDESTRIAN MOVEMENTS IN URBAN TRAFFIC WITH A MOBILE MULTI-SENSOR SYSTEM
by: B. Borgmann, et al.
Published: (2021-06-01) -
USAGE OF MULTIPLE LIDAR SENSORS ON A MOBILE SYSTEM FOR THE DETECTION OF PERSONS WITH IMPLICIT SHAPE MODELS
by: B. Borgmann, et al.
Published: (2018-05-01) -
TUM-MLS-2016: An Annotated Mobile LiDAR Dataset of the TUM City Campus for Semantic Point Cloud Interpretation in Urban Areas
by: Jingwei Zhu, et al.
Published: (2020-06-01)