RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

Automated monitoring and analysis of passenger movement in safety-critical parts of transport infrastructures represent a relevant visual surveillance task. Recent breakthroughs in visual representation learning and spatial sensing opened up new possibilities for detecting and tracking humans and objects within a 3D spatial context. This paper proposes a flexible analysis scheme and a thorough evaluation of various processing pipelines to detect and track humans on a ground plane, calibrated automatically via stereo depth and pedestrian detection. We consider multiple combinations within a set of RGB- and depth-based detection and tracking modalities. We exploit the modular concepts of Meshroom and demonstrate its use as a generic vision processing pipeline and scalable evaluation framework. Furthermore, we introduce a novel open RGB-D railway platform dataset with annotations to support research activities in automated RGB-D surveillance. We present quantitative results for multiple object detection and tracking for various algorithmic combinations on our dataset. Results indicate that the combined use of depth-based spatial information and learned representations yields substantially enhanced detection and tracking accuracies. As demonstrated, these enhancements are especially pronounced in adverse situations when occlusions and objects not captured by learned representations are present.
OriginalspracheEnglisch
TitelPattern Recognition. ICPR International Workshops and Challenges
Herausgeber (Verlag)Springer Nature
Seiten656-671
Seitenumfang16
Band12667
ISBN (elektronisch)978-3-030-68787-8
ISBN (Print)978-3-030-68786-1
DOIs
PublikationsstatusVeröffentlicht - 2021
VeranstaltungInternational Workshop on Research & Innovation for Secure Societies at the International Conference on Pattern Recognition ICPR 2020 -
Dauer: 10 Jan. 202115 Jan. 2021

Publikationsreihe

NameLecture Notes in Computer Science
Herausgeber (Verlag)Springer Nature
Band12667
ISSN (Print)0302-9743
ISSN (elektronisch)161-3349

Konferenz

KonferenzInternational Workshop on Research & Innovation for Secure Societies at the International Conference on Pattern Recognition ICPR 2020
Zeitraum10/01/2115/01/21

Research Field

  • Assistive and Autonomous Systems

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