Multi-Spectral Segmentation with Synthesized Data for Refuse Sorting

Harald Ganster, Alfred Rinnhofer, Georg Waltner, Christian Payer, Heimo Gursch, Christian Oberwinkler, Reinhard Meisenbichler, Horst Bischof

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung


Refuse sorting is a key technology to increase the recycling rate and reduce the growths of landfills worldwide. However, monitoring and parameterization of sorting facilities is still done in a mostly static fashion. This work combines multi-spectral imaging with deep learning based image recognition to monitor and dynamically optimize processes in sorting facilities.
Our solution is capable of monitoring the sorting process remotely avoiding potentially harmful working conditions due to dust, bacteria, and fungal spores. Furthermore, the introduction of objective sorting performance measures enables informed decisions to improve the sorting parameters and react quicker to changes in the refuse composition.
TitelProceedings of the OAGM Workshop 2021
Redakteure/-innenMarkus Seidl, Matthias Zeppelzauer, Peter M. Roth
Herausgeber (Verlag)Verlag der Technischen Universität Graz
PublikationsstatusVeröffentlicht - 2021
Veranstaltung44th OAGM Workshop 2021: Computer Vision and Pattern Analysis Across Domains: ÖAGM 2021 - University of Applied Sciences St. Pölten, abgesagt, Österreich
Dauer: 24 Nov. 202125 Nov. 2021


Konferenz44th OAGM Workshop 2021: Computer Vision and Pattern Analysis Across Domains


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