Robot painter: from object to trajectory
This paper presents visual perception discovered in high-level manipulator planning for a robot to reproduce the procedure involved in human painting. First, we propose a technique of 3D object segmentation that can work well even when the precision of the cameras is inadequate. Second, we apply a s...
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| creator | Ruchanurucks, M. Kudoh, S. Ogawara, K. Shiratori, T. Ikeuchi, K. |
| description | This paper presents visual perception discovered in high-level manipulator planning for a robot to reproduce the procedure involved in human painting. First, we propose a technique of 3D object segmentation that can work well even when the precision of the cameras is inadequate. Second, we apply a simple yet powerful fast color perception model that shows similarity to human perception. The method outperforms many existing interactive color perception algorithms. Third, we generate global orientation map perception using a radial basis function. Finally, we use the derived foreground, color segments, and orientation map to produce a visual feedback drawing Our main contributions are 3D object segmentation and color perception schemes. |
| doi_str_mv | 10.1109/IROS.2007.4399010 |
| format | Conference Proceeding |
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| ispartof | 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007, p.339-345 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Artificial intelligence color perception Data mining High-level planning Humans Image segmentation Intelligent robots Object segmentation orientation map Robot sensing systems Trajectory Visual perception |
| title | Robot painter: from object to trajectory |
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