Fachbereich Maschinenbau und Mechatronik
Refine
Year of publication
Institute
- Fachbereich Maschinenbau und Mechatronik (868)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (20)
- ECSM European Center for Sustainable Mobility (7)
- Fachbereich Elektrotechnik und Informationstechnik (6)
- Fachbereich Luft- und Raumfahrttechnik (6)
- IaAM - Institut für angewandte Automation und Mechatronik (4)
- Fachbereich Chemie und Biotechnologie (3)
- Fachbereich Medizintechnik und Technomathematik (2)
- Fachbereich Wirtschaftswissenschaften (2)
- Fachbereich Architektur (1)
Document Type
- Article (484)
- Conference Proceeding (207)
- Book (99)
- Part of a Book (32)
- Lecture (21)
- Report (8)
- Bachelor Thesis (5)
- Contribution to a Periodical (3)
- Doctoral Thesis (2)
- Master's Thesis (2)
Keywords
- Rapid Prototyping (8)
- Rapid prototyping (6)
- Übungsklausur (5)
- Additive manufacturing (4)
- Gamification (4)
- Fertigungsverfahren (3)
- Mikrosystemtechnik (3)
- Regelungstechnik (3)
- SLM (3)
- additive manufacturing (3)
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.