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Conference Paper
Synthetic Learning Set for Object Pose Estimation: Initial Experiments
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- Authors
- Joo-Haeng Lee, Woo-Han Yun, Jaeyeon Lee, Jaehong Kim
- Issue Date
- 2017-06
- Citation
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2017, pp.106-108
- Language
- English
- Type
- Conference Paper
- Project Code
- 17PS2200, Development of Modular Manipulation System Capable of Self-Reconfiguration of Control and Recognition System for Expansion of Robot Applicability, Kim Jae Hong
- Abstract
- We summarize a method to generate a synthetic learning set for object pose estimation in robotic manipulation tasks. Exploiting modern computer graphics techniques, our synthetic learning set satisfies the requirements both in quantitative diversity and qualitative precision. We report the partial results of initial experiments and discuss some future research directions.
- KSP Keywords
- Computer graphics, Future research directions, Object Pose Estimation, robotic manipulation