期刊论文详细信息
Proceedings of the XXth Conference of Open Innovations Association FRUCT
6D Pose Estimation of Transparent Object from Single RGB Image
Munkhtulga Byambaa1  Gou Koutaki1  Lodoiravsal Choimaa2 
[1] Kumamoto University, Kumamoto, Japan;National University of Mongolia, Ulaanbaatar, Mongolia;
关键词: pose estimation;    transparent object;    synthetic data;    deep neural network;   
DOI  :  
来源: DOAJ
【 摘 要 】

Transparent objects are one of the most common objects in everyday life. Estimating pose of these objects are required to pick and manipulate such objects. However, due to the absorption and refraction of light, it is hard to capture depth im- age of transparent object. In this paper, we address this problem using synthetic dataset to train deep neural network and estimate pose of known transparent objects. Synthetic dataset contains depth map of transparent object which we created in realistic looking environment. Also combining domain randomized and photorealistic images, we create desired amount of annotated data in order to network operate successfully against real world data. We conducted experiment on 3D printed transparent objects in the real environment. For future work, we are planning to build random bin picking system for transparent object.

【 授权许可】

Unknown   

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